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0;display:none;vertical-align:middle;outline:0;cursor:pointer}.lm-close-icon:after{content:'X';display:block;width:15px;height:15px;text-align:center;color:#000;font-weight:normal;font-size:12px;cursor:pointer}.lm-DockPanel{z-index:0}.lm-DockPanel-widget{z-index:0}.lm-DockPanel-tabBar{z-index:1}.lm-DockPanel-handle{z-index:2}.lm-DockPanel-handle.lm-mod-hidden{display:none!important}.lm-DockPanel-handle:after{position:absolute;top:0;left:0;width:100%;height:100%;content:''}.lm-DockPanel-handle[data-orientation='horizontal']{cursor:ew-resize}.lm-DockPanel-handle[data-orientation='vertical']{cursor:ns-resize}.lm-DockPanel-handle[data-orientation='horizontal']:after{left:50%;min-width:8px;transform:translateX(-50%)}.lm-DockPanel-handle[data-orientation='vertical']:after{top:50%;min-height:8px;transform:translateY(-50%)}.lm-DockPanel-overlay{z-index:3;box-sizing:border-box;pointer-events:none}
 .lm-DockPanel-overlay.lm-mod-hidden{display:none!important}.lm-Menu{z-index:10000;position:absolute;white-space:nowrap;overflow-x:hidden;overflow-y:auto;outline:0;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.lm-Menu-content{margin:0;padding:0;display:table;list-style-type:none}.lm-Menu-item{display:table-row}.lm-Menu-item.lm-mod-hidden,.lm-Menu-item.lm-mod-collapsed{display:none!important}.lm-Menu-itemIcon,.lm-Menu-itemSubmenuIcon{display:table-cell;text-align:center}.lm-Menu-itemLabel{display:table-cell;text-align:left}.lm-Menu-itemShortcut{display:table-cell;text-align:right}.lm-MenuBar{outline:0;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.lm-MenuBar-content{margin:0;padding:0;display:flex;flex-direction:row;list-style-type:none}.lm-MenuBar-item{box-sizing:border-box}.lm-MenuBar-itemIcon,.lm-MenuBar-itemLabel{display:inline-block}.lm-ScrollBar{display:flex;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.lm-ScrollBar[data-orientation='horizontal']{flex-direction:row}.lm-ScrollBar[data-orientation='vertical']{flex-direction:column}.lm-ScrollBar-button{box-sizing:border-box;flex:0 0 auto}.lm-ScrollBar-track{box-sizing:border-box;position:relative;overflow:hidden;flex:1 1 auto}.lm-ScrollBar-thumb{box-sizing:border-box;position:absolute}.lm-SplitPanel-child{z-index:0}.lm-SplitPanel-handle{z-index:1}.lm-SplitPanel-handle.lm-mod-hidden{display:none!important}.lm-SplitPanel-handle:after{position:absolute;top:0;left:0;width:100%;height:100%;content:''}.lm-SplitPanel[data-orientation='horizontal']>.lm-SplitPanel-handle{cursor:ew-resize}.lm-SplitPanel[data-orientation='vertical']>.lm-SplitPanel-handle{cursor:ns-resize}.lm-SplitPanel[data-orientation='horizontal']>.lm-SplitPanel-handle:after{left:50%;min-width:8px;transform:translateX(-50%)}.lm-SplitPanel[data-orientation='vertical']>.lm-SplitPanel-handle:after{top:50%;min-height:8px;transform:translateY(-50%)}.lm-TabBar{display:flex;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.lm-TabBar[data-orientation='horizontal']{flex-direction:row;align-items:flex-end}.lm-TabBar[data-orientation='vertical']{flex-direction:column;align-items:flex-end}.lm-TabBar-content{margin:0;padding:0;display:flex;flex:1 1 auto;list-style-type:none}.lm-TabBar[data-orientation='horizontal']>.lm-TabBar-content{flex-direction:row}.lm-TabBar[data-orientation='vertical']>.lm-TabBar-content{flex-direction:column}.lm-TabBar-tab{display:flex;flex-direction:row;box-sizing:border-box;overflow:hidden;touch-action:none}.lm-TabBar-tabIcon,.lm-TabBar-tabCloseIcon{flex:0 0 auto}.lm-TabBar-tabLabel{flex:1 1 auto;overflow:hidden;white-space:nowrap}.lm-TabBar-tabInput{user-select:all;width:100%;box-sizing:border-box}.lm-TabBar-tab.lm-mod-hidden{display:none!important}.lm-TabBar-addButton.lm-mod-hidden{display:none!important}.lm-TabBar.lm-mod-dragging .lm-TabBar-tab{position:relative}.lm-TabBar.lm-mod-dragging[data-orientation='horizontal'] .lm-TabBar-tab{left:0;transition:left 150ms ease}.lm-TabBar.lm-mod-dragging[data-orientation='vertical'] .lm-TabBar-tab{top:0;transition:top 150ms ease}.lm-TabBar.lm-mod-dragging .lm-TabBar-tab.lm-mod-dragging{transition:none}.lm-TabBar-tabLabel 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> On our ACL Best Paper Award Paper | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="a short philosophical discursion"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/blog/2024/best_paper/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item active"> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">On our ACL Best Paper Award Paper</h1> <p class="post-meta"> Created in August 07, 2024 </p> <p class="post-tags"> <a href="/blog/2024"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </a>   ·   <a href="/blog/tag/formatting"> <i class="fa-solid fa-hashtag fa-sm"></i> formatting</a>   <a href="/blog/tag/links"> <i class="fa-solid fa-hashtag fa-sm"></i> links</a>   ·   <a href="/blog/category/sample-posts"> <i class="fa-solid fa-tag fa-sm"></i> sample-posts</a> </p> </header> <article class="post-content"> <div id="markdown-content"> <p>Yesterday, my student Liang (Leon) Lu won the Best Paper Award (Non-Publicized) at the 2024 Association for Computational Linguistics conference in Bangkok for his paper “Semisupervised Neural Proto-Language Reconstruction.” We are generally impressed by students who win this awards, but in Leon’s case their is double reason to be impressed. Not only is he an undergraduate student (just starting his third year of university), he has only submitted two papers to conferences. Both were accepted and the second (his first submission to a *ACL conference) was the subject of this best paper award. But what is the substance of this paper?</p> <p>If you are technical, you can go and read the paper for yourself. It is short and is, I think, fairly clearly written. If you are not technical but you have some training in historical linguistics, you will recognize some of the principal themes, even if you don’t follow the complete methodology or analysis. However, if you are neither technical nor trained in historical linguistics, but you still want to know what this paper was about, I will do me best to let you know.</p> <p>First, let us consider a table of words from the related languages Kachai, Huishu, and Ukhrul (members of the family of languages called Tangkhulic):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> </table> <p>Note that the ð sound is like the th in <em>this</em> and the ɐ sound is sort of like the u in cup.</p> <p>If you look at these words, you can see that there is, for example, a systematic relationship between the words for ‘bone‘ and those for ‘breast’. This extends to ‘grandchild’ as well, even though there is a somewhat unexpected consonant in Kachai (ð). What did the ancestors of these words look like in the shared ancestor of these languages? Is this lost in the mists of history?</p> <p>A group of 19th century linguists (of philologists, to use the terminology then current) called the Neogrammarians said you can know how these ancestral forms of words (protoforms) were pronounced by applying a methodology we now call the Comparative Method. Central to this method is the <strong>regularity principle</strong> which states that changes in pronunciation apply as general rules to which <strong>all</strong> words in a language are subject. This means that if you know the protoform for one of the columns in the table (these columns are what are known as “cognate sets”) you can derive all of the rows in that column deterministically—mechanically and unambiguously.</p> <p>Under these Neogrammarian assumptions, we could posit *ruk or *ru as reconstructions for ‘bone’. If we posit *ru, we must assert that there was a sound change in Kachai that changed u to ɐ and a sound change in Huishu that inserted k at the ends of words (perhaps after u). If we reconstruction *ruk, we have to assume that there was a sound change in both Kachai and Ukhrul that deletes k at the end of words (perhaps after u) and another sound change in Kachai that changes u to ɐ. The first option (*ru) ends up working better if we look at all of the cognate sets instead of just these four.</p> <p>By this logic, we get:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*?u</td> <td>*ru</td> <td>*nu</td> <td>*n?</td> </tr> </tbody> </table> <p>The reconstruction of ‘grandchild’ must end in u, but it must start with something other than r. Why? Because if it did start with r, there would be no way of explaining why, in Kachai, ‘grandchild’ starts with ð but ‘bone’ starts with r through the application of regular sound change. This would be an <strong>unconditioned split</strong>, something that the regularity principle rules out.</p> <p>Looking at the full collection of cognate sets, we would probably make the following reconstructions (or their formal equivalents):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td>*nɨ</td> </tr> </tbody> </table> <p>where ɨ is a vowel that is half-way between i and u. These protoforms make sense based on the reflexes: they are similar in pronunciation to the reflexes and the reflexes can all be derived from them mechanically.</p> <p>There have been past efforts to build neural models (neural networks) that can perform this kind of reconstruction (including some from our lab), but they have two unfortunate properties:</p> <ol> <li>They only take the reflex-to-protoform mapping into account (not the protoform-to-reflex mapping).</li> <li>Training them (teaching them to generate reconstructions given sets of cognate reflexes) requires many cognate sets, each of which must be paired with a reconstruction.</li> </ol> <p>In actual reconstruction projects, as I know from first hand experience, the constraint in 2 is only satisfied when the most challenging and interesting work in reconstructing a protolanguage has already been done. What Leon discovered as part of this paper is that 2 is a consequence of 1—we are forced to do fully supervised training (a protoform for every cognate set) because we are not enforcing the regularity principle (not rejecting protoforms if—for example—identical protoforms are mapped to different reflex forms in a single language).</p> <p>To make things clearer, let’s return to our example. The older kind of fully-supervised reconstruction models is likely to produce the reconstructions below:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td><strong>*nu</strong></td> </tr> </tbody> </table> <p>This is because having a u in Ukhrul and a u in Huishu is generally a reliable cue for reconstructing *u in the protoform. However, this reconstruction cannot be right, following the regularity principle, because a single pronunciation in the protolanguage would be reflected as two different pronunciations in Kachai.</p> <p>Leon’s technical innovation was to design a neural network that can learn both to reconstruct protoforms based on reflexes (daughter-to-protoform) and to disfavor protoforms from which reflexes cannot be derived (proto-to-daughter). The D2P and P2D networks are joined together with a “bridge network” that allows both networks to be trained as a single network. The resulting type of neural network is similar in some ways to what is called a “variational autoencoder” but it differs in that the outputs of the D2P network are not real-valued vectors but strings of symbols (in the International Phonetic Alphabet).</p> <p>In training, the model can thus take advantage of cognate sets without a protoform, something that the earlier, fully supervised, models could not do.</p> <p>The implications of this development are striking. Given the same amount of labeled data (cognate sets with protoforms), our DPD models outperform the best fully supervised models as well as the best semisupervised models we could train. And careful statistical testing shows that the differences are as significant as they look at first glance.</p> <p>We think that this approach is very promising and looks forward to a day, not too far in the future, when neural models like this will be a tool in the belt of every historical linguist and will help shed light on the dark recesses of the human past.</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/why-diachronic-linguistics/">Why does diachronic linguistics matter?</a> </li> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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Not only is he an undergraduate student (just starting his third year of university), he has only submitted two papers to conferences. Both were accepted and the second (his first submission to a *ACL conference) was the subject of this best paper award. But what is the substance of this paper?</p> <p>If you are technical, you can go and read the paper for yourself. It is short and is, I think, fairly clearly written. If you are not technical but you have some training in historical linguistics, you will recognize some of the principal themes, even if you don’t follow the complete methodology or analysis. However, if you are neither technical nor trained in historical linguistics, but you still want to know what this paper was about, I will do me best to let you know.</p> <p>First, let us consider a table of words from the related languages Kachai, Huishu, and Ukhrul (members of the family of languages called Tangkhulic):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> </table> <p>Note that the ð sound is like the th in <em>this</em> and the ɐ sound is sort of like the u in cup.</p> <p>If you look at these words, you can see that there is, for example, a systematic relationship between the words for ‘bone‘ and those for ‘breast’. This extends to ‘grandchild’ as well, even though there is a somewhat unexpected consonant in Kachai (ð). What did the ancestors of these words look like in the shared ancestor of these languages? Is this lost in the mists of history?</p> <p>A group of 19th century linguists (of philologists, to use the terminology then current) called the Neogrammarians said you can know how these ancestral forms of words (protoforms) were pronounced by applying a methodology we now call the Comparative Method. Central to this method is the <strong>regularity principle</strong> which states that changes in pronunciation apply as general rules to which <strong>all</strong> words in a language are subject. This means that if you know the protoform for one of the columns in the table (these columns are what are known as “cognate sets”) you can derive all of the rows in that column deterministically—mechanically and unambiguously.</p> <p>Under these Neogrammarian assumptions, we could posit *ruk or *ru as reconstructions for ‘bone’. If we posit *ru, we must assert that there was a sound change in Kachai that changed u to ɐ and a sound change in Huishu that inserted k at the ends of words (perhaps after u). If we reconstruction *ruk, we have to assume that there was a sound change in both Kachai and Ukhrul that deletes k at the end of words (perhaps after u) and another sound change in Kachai that changes u to ɐ. The first option (*ru) ends up working better if we look at all of the cognate sets instead of just these four.</p> <p>By this logic, we get:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*?u</td> <td>*ru</td> <td>*nu</td> <td>*n?</td> </tr> </tbody> </table> <p>The reconstruction of ‘grandchild’ must end in u, but it must start with something other than r. Why? Because if it did start with r, there would be no way of explaining why, in Kachai, ‘grandchild’ starts with ð but ‘bone’ starts with r through the application of regular sound change. This would be an <strong>unconditioned split</strong>, something that the regularity principle rules out.</p> <p>Looking at the full collection of cognate sets, we would probably make the following reconstructions (or their formal equivalents):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td>*nɨ</td> </tr> </tbody> </table> <p>where ɨ is a vowel that is half-way between i and u. These protoforms make sense based on the reflexes: they are similar in pronunciation to the reflexes and the reflexes can all be derived from them mechanically.</p> <p>There have been past efforts to build neural models (neural networks) that can perform this kind of reconstruction (including some from our lab), but they have two unfortunate properties:</p> <ol> <li>They only take the reflex-to-protoform mapping into account (not the protoform-to-reflex mapping).</li> <li>Training them (teaching them to generate reconstructions given sets of cognate reflexes) requires many cognate sets, each of which must be paired with a reconstruction.</li> </ol> <p>In actual reconstruction projects, as I know from first hand experience, the constraint in 2 is only satisfied when the most challenging and interesting work in reconstructing a protolanguage has already been done. What Leon discovered as part of this paper is that 2 is a consequence of 1—we are forced to do fully supervised training (a protoform for every cognate set) because we are not enforcing the regularity principle (not rejecting protoforms if—for example—identical protoforms are mapped to different reflex forms in a single language).</p> <p>To make things clearer, let’s return to our example. The older kind of fully-supervised reconstruction models is likely to produce the reconstructions below:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td><strong>*nu</strong></td> </tr> </tbody> </table> <p>This is because having a u in Ukhrul and a u in Huishu is generally a reliable cue for reconstructing *u in the protoform. However, this reconstruction cannot be right, following the regularity principle, because a single pronunciation in the protolanguage would be reflected as two different pronunciations in Kachai.</p> <p>Leon’s technical innovation was to design a neural network that can learn both to reconstruct protoforms based on reflexes (daughter-to-protoform) and to disfavor protoforms from which reflexes cannot be derived (proto-to-daughter). The D2P and P2D networks are joined together with a “bridge network” that allows both networks to be trained as a single network. The resulting type of neural network is similar in some ways to what is called a “variational autoencoder” but it differs in that the outputs of the D2P network are not real-valued vectors but strings of symbols (in the International Phonetic Alphabet).</p> <p>In training, the model can thus take advantage of cognate sets without a protoform, something that the earlier, fully supervised, models could not do.</p> <p>The implications of this development are striking. Given the same amount of labeled data (cognate sets with protoforms), our DPD models outperform the best fully supervised models as well as the best semisupervised models we could train. And careful statistical testing shows that the differences are as significant as they look at first glance.</p> <p>We think that this approach is very promising and looks forward to a day, not too far in the future, when neural models like this will be a tool in the belt of every historical linguist and will help shed light on the dark recesses of the human past.</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/cl_in_acl/">Is ACL an AI (or NLP or CL) Conference?</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/why-diachronic-linguistics/">Why does diachronic linguistics matter?</a> </li> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Is ACL an AI (or NLP or CL) Conference? | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Ruminations on Emily Bender's Presidential Address at ACL2024"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/blog/2024/cl_in_acl/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item active"> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Is ACL an AI (or NLP or CL) Conference?</h1> <p class="post-meta"> Created in August 07, 2024 </p> <p class="post-tags"> <a href="/blog/2024"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </a>   ·   <a href="/blog/tag/formatting"> <i class="fa-solid fa-hashtag fa-sm"></i> formatting</a>   <a href="/blog/tag/links"> <i class="fa-solid fa-hashtag fa-sm"></i> links</a>   ·   <a href="/blog/category/sample-posts"> <i class="fa-solid fa-tag fa-sm"></i> sample-posts</a> </p> </header> <article class="post-content"> <div id="markdown-content"> <p><a href="/assets/img/acl_is_not_ai_conference.jpg"></a></p> <p>In the title of a controversial Presidential Address at ACL2024, Emily Bender proclaimed that “ACL is not an AI conference.“ I was not fortunate enough to be in Bangkok to hear the address, but I have read the slides and, since it concerns me personally, I want to write a short response.</p> <p>tl;dr Reinforcing disciplinary boundaries between CL, NLP, and ML makes all three disciplines poorer and less coherent. They <strong>all</strong> belong at ACL. As for “AI,” it is not a discipline but a marketing term and contrasting it with the big three is a category error.</p> <p>I am a Computational Linguist who is deeply embedded in the ACL community. I am not alone. People who try to paint ACL as an NLP conference only (e.g., Yoav Goldberg) are ignored the substantial number of CL scientists who participate in ACL in all capacities and the role that CL has always played in the *ACL organizations and conferences. Bender commits the same type of error when she tries to exclude or marginalize “AI,” by which I assume she means machine learning. This is problematic in a couple of respects:</p> <ol> <li> <strong>AI is not a discipline, technology, community, or anything substantial at all—it is a marketing term.</strong> One might as coherently say that ACL is not a phlogiston conference as to say that it is not an “AI” conference. AI has referred to symbolic systems like the HPSG grammars for which Bender is well known, expert systems, behavior trees guiding video game characters, classical statistical machine learning, perceptrons, deep neural nets, language models, and so on. AI is just “computers looking smart so you’ll give us money” and not anything a conference could be about.</li> <li>If she means “machine learning” then, in a sense, she’s right—almost no one believes that ACL is a machine learning conference in the sense that ICML, ICLR, and NeurIPS are. However, <strong>to exclude work from the conference that is focused on ML techniques (which are thoroughly embedded in modern NLP and CL) would make the community vastly poorer.</strong> And there is no reason that ACL cannot be a CL conference, and NLP conference, and an ML conference. These fields intersect and reinforce each other and well all benefit from interacting (and even confronting) one another.</li> </ol> <p>I understand one of Bender’s points: many younger reviewers, even in linguistics-heavy tracks like Linguistic Theories and Cognitive Modeling and Phonology, Morphology, and Word Segmentation, will criticize papers for lacking novelty (really technical novelty) when they concentrate on answering a scientific question about language (or a language) rather than presenting a technical innovation. I’ve encountered this when writing metareviews as an AC and AE. I’ve also encountered it first hand. For example, I once received a very low review on a linguistics paper submitted to a *ACL because the ML techniques used were well-known (decision trees, SVMs, and generic LSTMs and CNNs). The reviewer, apparently not familiar with linguistic research, missed our point, which is that these tools resolved a theoretically significant question about the languages under investigation. (Ironically, another reviewer attacked us for ignoring linguistic theory because our findings did not accord with their theoretical preconceptions). In this case, as in many cases I’ve seen, an AC with a broader view of the field(s) stepped in and wrote a balanced and informed metareview. This is not to say that the system is perfect; only that overly strong statements about linguistics being pushed out of ACL by AI-intoxicated reviewers are not helpful.</p> <p>In fact, there is no reason for linguistics, as a field, to be at odds with ML. The animosity, I think, comes from the incompatibility of a certain <strong>kind</strong> of linguistics with a particular <strong>kind</strong> of machine learning researcher. Starting in the 1950s, North American linguistics was dominated by the generative school, which was built upon discrete symbolic representations governed by categorical rules and constraints and arrived at via a specific introspective methodology. This was compatible with (indeed, very much a part) of the first wave of “artificial intelligence” research. Head Driven Phrase Structure Grammar (on which Bender cut her teeth) grows out of this school (though it has a more computationally appealing formalism and a more empirically-oriented culture). But generative linguistics is not (and has never been) the only approached to the language sciences. Many linguists before, during, and after the heyday of generative grammar, have viewed language as grounded in stochastic patterns of usage and for these empirically-minded linguists, machine learning (whether classical or neural) is a natural, intuitive approach to language.</p> <p>The point of disagreement, really, is in what class of questions are interesting. Few linguists (even computational linguists) are really going be interested in knowledge distillation and few ML practitioners are really going to be interested in noncompositionality in Newari noun phrases. I would like to advance the radical proposition that it is okay for a professional organization and a conference to embrace people who are interested in different things. I would go further and say that we benefit from being in an organization with people who have different interests and backgrounds than we have. In the end, we all have language to tie us together, and we all have computing to tie us together.</p> <p>I sincerely believe that the name of the ACL should change. We should keep “ACL” but change the full name to “<strong>the Association for Computing and Language</strong>.” This matched better what the ACL is to me and sets the tenor for a community that embraces a spectrum of research interests and practices.</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/why-diachronic-linguistics/">Why does diachronic linguistics matter?</a> </li> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Why does diachronic linguistics matter? | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="a short philosophical discursion"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/blog/2024/why-diachronic-linguistics/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item active"> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Why does diachronic linguistics matter?</h1> <p class="post-meta"> Created in August 07, 2024 </p> <p class="post-tags"> <a href="/blog/2024"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </a>   ·   <a href="/blog/tag/formatting"> <i class="fa-solid fa-hashtag fa-sm"></i> formatting</a>   <a href="/blog/tag/links"> <i class="fa-solid fa-hashtag fa-sm"></i> links</a>   ·   <a href="/blog/category/sample-posts"> <i class="fa-solid fa-tag fa-sm"></i> sample-posts</a> </p> </header> <article class="post-content"> <div id="markdown-content"> <p>Diachronic linguistics is important for the same reason the evolutionary biology is important: you cannot really understand the state of a language at any given time, or why the range of attested languages is what it is, without understanding the mechanisms by which languages come to be.</p> <p>In computational linguistics, diachrony has often played second fiddle. The focus, during the Age of Rules, was on implementing linguistic formalisms (that captured aspects of language like syntax, semantics, and discourse structure). This reflected the prestige approaches in theoretical linguistics. It also reflected the underlying expectation that, with just a few more rules (or a few more fixes to existing rules), these symbolic systems would be good for something.</p> <p>Historical linguistics has long lacked the prestige of theoretical syntax and semantics and, at first blush, it is not good for much in the practical realm. Certainly the knowledge of human history and culture that comes from understanding the linguistic past is valuable. However, it is not readily apparent how diachronic linguistics feeds into machine translation, question answering, automatic speech recognition, or any of the other human language technologies that are economically important today.</p> <p>Certainly, on the margins, historical linguistics can help with a few NLP tasks. For example, historical linguistic relationships (are the resulting similarities in phonology) can be leveraged to facilitate named entity recognition, as we have shown in a few papers like <a class="citation" href="#bharadwaj2016phonologically">(Bharadwaj et al., 2016)</a> and <a class="citation" href="#chaudhary2018adapting">(Chaudhary et al., 2018)</a>. Likewise, phylogentitic information has been used for selecting transfer languages in cross-lingual training. However, it seems unlikely that the next big breakthrough in NLP will be the product of diachronic linguistics (or even linguistics).</p> <p>What it lacks in terms of engineering potential, though, diachronic linguistics more than makes up for in its scientific implications. Indeed, the persistent question of typology (why languages are so alike and why they differ where they differ) has been treated as a question of human linguistic competence. However, decades of research make it appear more likely that it is the mechanisms of human change the bias languages towards certain structural properties, whether in phonology, morphology, syntax, semantics, etc. The question of why languages vary in the way that they do, then, is ultimately a question of what changes languages are likely to undergo in their histories.</p> <p>It is not obvious that diachronic linguistics will have a transformative affect upon the world economy or the technological sphere. However, it is almost certain that our understanding of human language as a phenomenon hinges on our understanding of language change and linguistic history. This may, in turn, have practical consequences, but <strong>even if it does not</strong> investigating linguistic diachrony is worthwhile.</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </li> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Why does diachronic linguistics matter? | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="a short philosophical discursion"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/blog/2024/why-diachronic-linguistics/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item active"> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Why does diachronic linguistics matter?</h1> <p class="post-meta"> Created in August 07, 2024 </p> <p class="post-tags"> <a href="/blog/2024"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </a>   ·   <a href="/blog/tag/formatting"> <i class="fa-solid fa-hashtag fa-sm"></i> formatting</a>   <a href="/blog/tag/links"> <i class="fa-solid fa-hashtag fa-sm"></i> links</a>   ·   <a href="/blog/category/sample-posts"> <i class="fa-solid fa-tag fa-sm"></i> sample-posts</a> </p> </header> <article class="post-content"> <div id="markdown-content"> <p>Diachronic linguistics is important for the same reason the evolutionary biology is important: you cannot really understand the state of a language at any given time, or why the range of attested languages is what it is, without understanding the mechanisms by which languages come to be.</p> <p>In computational linguistics, diachrony has often played second fiddle. The focus, during the Age of Rules, was on implementing linguistic formalisms (that captured aspects of language like syntax, semantics, and discourse structure). This reflected the prestige approaches in theoretical linguistics. It also reflected the underlying expectation that, with just a few more rules (or a few more fixes to existing rules), these symbolic systems would be good for something.</p> <p>Historical linguistics has long lacked the prestige of theoretical syntax and semantics and, at first blush, it is not good for much in the practical realm. Certainly the knowledge of human history and culture that comes from understanding the linguistic past is valuable. However, it is not readily apparent how diachronic linguistics feeds into machine translation, question answering, automatic speech recognition, or any of the other human language technologies that are economically important today.</p> <p>Certainly, on the margins, historical linguistics can help with a few NLP tasks. For example, historical linguistic relationships (are the resulting similarities in phonology) can be leveraged to facilitate named entity recognition, as we have shown in a few papers like <a class="citation" href="#bharadwaj2016phonologically">(Bharadwaj et al., 2016)</a> and <a class="citation" href="#chaudhary2018adapting">(Chaudhary et al., 2018)</a>. Likewise, phylogentitic information has been used for selecting transfer languages in cross-lingual training. However, it seems unlikely that the next big breakthrough in NLP will be the product of diachronic linguistics (or even linguistics).</p> <p>What it lacks in terms of engineering potential, though, diachronic linguistics more than makes up for in its scientific implications. Indeed, the persistent question of typology (why languages are so alike and why they differ where they differ) has been treated as a question of human linguistic competence. However, decades of research make it appear more likely that it is the mechanisms of human change the bias languages towards certain structural properties, whether in phonology, morphology, syntax, semantics, etc. The question of why languages vary in the way that they do, then, is ultimately a question of what changes languages are likely to undergo in their histories.</p> <p>It is not obvious that diachronic linguistics will have a transformative affect upon the world economy or the technological sphere. However, it is almost certain that our understanding of human language as a phenomenon hinges on our understanding of language change and linguistic history. This may, in turn, have practical consequences, but <strong>even if it does not</strong> investigating linguistic diachrony is worthwhile.</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/cl_in_acl/">Is ACL an AI (or NLP or CL) Conference?</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </li> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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-<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.3">Jekyll</generator><link href="https://changelinglab.github.io/feed.xml" rel="self" type="application/atom+xml"/><link href="https://changelinglab.github.io/" rel="alternate" type="text/html" hreflang="en"/><updated>2024-08-15T19:27:06+00:00</updated><id>https://changelinglab.github.io/feed.xml</id><title type="html">blank</title><subtitle>The CMU Language Change and Empirical Linguistics Lab </subtitle><entry><title type="html">Why does diachronic linguistics matter?</title><link href="https://changelinglab.github.io/blog/2024/why-diachronic-linguistics/" rel="alternate" type="text/html" title="Why does diachronic linguistics matter?"/><published>2024-08-07T16:40:16+00:00</published><updated>2024-08-07T16:40:16+00:00</updated><id>https://changelinglab.github.io/blog/2024/why-diachronic-linguistics</id><content type="html" xml:base="https://changelinglab.github.io/blog/2024/why-diachronic-linguistics/"><![CDATA[<p>Diachronic linguistics is important for the same reason the evolutionary biology is important: you cannot really understand the state of a language at any given time, or why the range of attested languages is what it is, without understanding the mechanisms by which languages come to be.</p> <p>In computational linguistics, diachrony has often played second fiddle. The focus, during the Age of Rules, was on implementing linguistic formalisms (that captured aspects of language like syntax, semantics, and discourse structure). This reflected the prestige approaches in theoretical linguistics. It also reflected the underlying expectation that, with just a few more rules (or a few more fixes to existing rules), these symbolic systems would be good for something.</p> <p>Historical linguistics has long lacked the prestige of theoretical syntax and semantics and, at first blush, it is not good for much in the practical realm. Certainly the knowledge of human history and culture that comes from understanding the linguistic past is valuable. However, it is not readily apparent how diachronic linguistics feeds into machine translation, question answering, automatic speech recognition, or any of the other human language technologies that are economically important today.</p> <p>Certainly, on the margins, historical linguistics can help with a few NLP tasks. For example, historical linguistic relationships (are the resulting similarities in phonology) can be leveraged to facilitate named entity recognition, as we have shown in a few papers like <a class="citation" href="#bharadwaj2016phonologically">(Bharadwaj et al., 2016)</a> and <a class="citation" href="#chaudhary2018adapting">(Chaudhary et al., 2018)</a>. Likewise, phylogentitic information has been used for selecting transfer languages in cross-lingual training. However, it seems unlikely that the next big breakthrough in NLP will be the product of diachronic linguistics (or even linguistics).</p> <p>What it lacks in terms of engineering potential, though, diachronic linguistics more than makes up for in its scientific implications. Indeed, the persistent question of typology (why languages are so alike and why they differ where they differ) has been treated as a question of human linguistic competence. However, decades of research make it appear more likely that it is the mechanisms of human change the bias languages towards certain structural properties, whether in phonology, morphology, syntax, semantics, etc. The question of why languages vary in the way that they do, then, is ultimately a question of what changes languages are likely to undergo in their histories.</p> <p>It is not obvious that diachronic linguistics will have a transformative affect upon the world economy or the technological sphere. However, it is almost certain that our understanding of human language as a phenomenon hinges on our understanding of language change and linguistic history. This may, in turn, have practical consequences, but <strong>even if it does not</strong> investigating linguistic diachrony is worthwhile.</p>]]></content><author><name></name></author><category term="sample-posts"/><category term="formatting"/><category term="links"/><summary type="html"><![CDATA[a short philosophical discursion]]></summary></entry><entry><title type="html">On our ACL Best Paper Award Paper</title><link href="https://changelinglab.github.io/blog/2024/best_paper/" rel="alternate" type="text/html" title="On our ACL Best Paper Award Paper"/><published>2024-08-07T16:40:16+00:00</published><updated>2024-08-07T16:40:16+00:00</updated><id>https://changelinglab.github.io/blog/2024/best_paper</id><content type="html" xml:base="https://changelinglab.github.io/blog/2024/best_paper/"><![CDATA[<p>Yesterday, my student Liang (Leon) Lu won the Best Paper Award (Non-Publicized) at the 2024 Association for Computational Linguistics conference in Bangkok for his paper “Semisupervised Neural Proto-Language Reconstruction.” We are generally impressed by students who win this awards, but in Leon’s case their is double reason to be impressed. Not only is he an undergraduate student (just starting his third year of university), he has only submitted two papers to conferences. Both were accepted and the second (his first submission to a *ACL conference) was the subject of this best paper award. But what is the substance of this paper?</p> <p>If you are technical, you can go and read the paper for yourself. It is short and is, I think, fairly clearly written. If you are not technical but you have some training in historical linguistics, you will recognize some of the principal themes, even if you don’t follow the complete methodology or analysis. However, if you are neither technical nor trained in historical linguistics, but you still want to know what this paper was about, I will do me best to let you know.</p> <p>First, let us consider a table of words from the related languages Kachai, Huishu, and Ukhrul (members of the family of languages called Tangkhulic):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> </table> <p>Note that the ð sound is like the th in <em>this</em> and the ɐ sound is sort of like the u in cup.</p> <p>If you look at these words, you can see that there is, for example, a systematic relationship between the words for ‘bone‘ and those for ‘breast’. This extends to ‘grandchild’ as well, even though there is a somewhat unexpected consonant in Kachai (ð). What did the ancestors of these words look like in the shared ancestor of these languages? Is this lost in the mists of history?</p> <p>A group of 19th century linguists (of philologists, to use the terminology then current) called the Neogrammarians said you can know how these ancestral forms of words (protoforms) were pronounced by applying a methodology we now call the Comparative Method. Central to this method is the <strong>regularity principle</strong> which states that changes in pronunciation apply as general rules to which <strong>all</strong> words in a language are subject. This means that if you know the protoform for one of the columns in the table (these columns are what are known as “cognate sets”) you can derive all of the rows in that column deterministically—mechanically and unambiguously.</p> <p>Under these Neogrammarian assumptions, we could posit *ruk or *ru as reconstructions for ‘bone’. If we posit *ru, we must assert that there was a sound change in Kachai that changed u to ɐ and a sound change in Huishu that inserted k at the ends of words (perhaps after u). If we reconstruction *ruk, we have to assume that there was a sound change in both Kachai and Ukhrul that deletes k at the end of words (perhaps after u) and another sound change in Kachai that changes u to ɐ. The first option (*ru) ends up working better if we look at all of the cognate sets instead of just these four.</p> <p>By this logic, we get:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*?u</td> <td>*ru</td> <td>*nu</td> <td>*n?</td> </tr> </tbody> </table> <p>The reconstruction of ‘grandchild’ must end in u, but it must start with something other than r. Why? Because if it did start with r, there would be no way of explaining why, in Kachai, ‘grandchild’ starts with ð but ‘bone’ starts with r through the application of regular sound change. This would be an <strong>unconditioned split</strong>, something that the regularity principle rules out.</p> <p>Looking at the full collection of cognate sets, we would probably make the following reconstructions (or their formal equivalents):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td>*nɨ</td> </tr> </tbody> </table> <p>where ɨ is a vowel that is half-way between i and u. These protoforms make sense based on the reflexes: they are similar in pronunciation to the reflexes and the reflexes can all be derived from them mechanically.</p> <p>There have been past efforts to build neural models (neural networks) that can perform this kind of reconstruction (including some from our lab), but they have two unfortunate properties:</p> <ol> <li>They only take the reflex-to-protoform mapping into account (not the protoform-to-reflex mapping).</li> <li>Training them (teaching them to generate reconstructions given sets of cognate reflexes) requires many cognate sets, each of which must be paired with a reconstruction.</li> </ol> <p>In actual reconstruction projects, as I know from first hand experience, the constraint in 2 is only satisfied when the most challenging and interesting work in reconstructing a protolanguage has already been done. What Leon discovered as part of this paper is that 2 is a consequence of 1—we are forced to do fully supervised training (a protoform for every cognate set) because we are not enforcing the regularity principle (not rejecting protoforms if—for example—identical protoforms are mapped to different reflex forms in a single language).</p> <p>To make things clearer, let’s return to our example. The older kind of fully-supervised reconstruction models is likely to produce the reconstructions below:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td><strong>*nu</strong></td> </tr> </tbody> </table> <p>This is because having a u in Ukhrul and a u in Huishu is generally a reliable cue for reconstructing *u in the protoform. However, this reconstruction cannot be right, following the regularity principle, because a single pronunciation in the protolanguage would be reflected as two different pronunciations in Kachai.</p> <p>Leon’s technical innovation was to design a neural network that can learn both to reconstruct protoforms based on reflexes (daughter-to-protoform) and to disfavor protoforms from which reflexes cannot be derived (proto-to-daughter). The D2P and P2D networks are joined together with a “bridge network” that allows both networks to be trained as a single network. The resulting type of neural network is similar in some ways to what is called a “variational autoencoder” but it differs in that the outputs of the D2P network are not real-valued vectors but strings of symbols (in the International Phonetic Alphabet).</p> <p>In training, the model can thus take advantage of cognate sets without a protoform, something that the earlier, fully supervised, models could not do.</p> <p>The implications of this development are striking. Given the same amount of labeled data (cognate sets with protoforms), our DPD models outperform the best fully supervised models as well as the best semisupervised models we could train. And careful statistical testing shows that the differences are as significant as they look at first glance.</p> <p>We think that this approach is very promising and looks forward to a day, not too far in the future, when neural models like this will be a tool in the belt of every historical linguist and will help shed light on the dark recesses of the human past.</p>]]></content><author><name></name></author><category term="sample-posts"/><category term="formatting"/><category term="links"/><summary type="html"><![CDATA[a short philosophical discursion]]></summary></entry></feed>
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.3.3">Jekyll</generator><link href="https://changelinglab.github.io/feed.xml" rel="self" type="application/atom+xml"/><link href="https://changelinglab.github.io/" rel="alternate" type="text/html" hreflang="en"/><updated>2024-08-15T19:41:14+00:00</updated><id>https://changelinglab.github.io/feed.xml</id><title type="html">blank</title><subtitle>The CMU Language Change and Empirical Linguistics Lab </subtitle><entry><title type="html">Why does diachronic linguistics matter?</title><link href="https://changelinglab.github.io/blog/2024/why-diachronic-linguistics/" rel="alternate" type="text/html" title="Why does diachronic linguistics matter?"/><published>2024-08-07T16:40:16+00:00</published><updated>2024-08-07T16:40:16+00:00</updated><id>https://changelinglab.github.io/blog/2024/why-diachronic-linguistics</id><content type="html" xml:base="https://changelinglab.github.io/blog/2024/why-diachronic-linguistics/"><![CDATA[<p>Diachronic linguistics is important for the same reason the evolutionary biology is important: you cannot really understand the state of a language at any given time, or why the range of attested languages is what it is, without understanding the mechanisms by which languages come to be.</p> <p>In computational linguistics, diachrony has often played second fiddle. The focus, during the Age of Rules, was on implementing linguistic formalisms (that captured aspects of language like syntax, semantics, and discourse structure). This reflected the prestige approaches in theoretical linguistics. It also reflected the underlying expectation that, with just a few more rules (or a few more fixes to existing rules), these symbolic systems would be good for something.</p> <p>Historical linguistics has long lacked the prestige of theoretical syntax and semantics and, at first blush, it is not good for much in the practical realm. Certainly the knowledge of human history and culture that comes from understanding the linguistic past is valuable. However, it is not readily apparent how diachronic linguistics feeds into machine translation, question answering, automatic speech recognition, or any of the other human language technologies that are economically important today.</p> <p>Certainly, on the margins, historical linguistics can help with a few NLP tasks. For example, historical linguistic relationships (are the resulting similarities in phonology) can be leveraged to facilitate named entity recognition, as we have shown in a few papers like <a class="citation" href="#bharadwaj2016phonologically">(Bharadwaj et al., 2016)</a> and <a class="citation" href="#chaudhary2018adapting">(Chaudhary et al., 2018)</a>. Likewise, phylogentitic information has been used for selecting transfer languages in cross-lingual training. However, it seems unlikely that the next big breakthrough in NLP will be the product of diachronic linguistics (or even linguistics).</p> <p>What it lacks in terms of engineering potential, though, diachronic linguistics more than makes up for in its scientific implications. Indeed, the persistent question of typology (why languages are so alike and why they differ where they differ) has been treated as a question of human linguistic competence. However, decades of research make it appear more likely that it is the mechanisms of human change the bias languages towards certain structural properties, whether in phonology, morphology, syntax, semantics, etc. The question of why languages vary in the way that they do, then, is ultimately a question of what changes languages are likely to undergo in their histories.</p> <p>It is not obvious that diachronic linguistics will have a transformative affect upon the world economy or the technological sphere. However, it is almost certain that our understanding of human language as a phenomenon hinges on our understanding of language change and linguistic history. This may, in turn, have practical consequences, but <strong>even if it does not</strong> investigating linguistic diachrony is worthwhile.</p>]]></content><author><name></name></author><category term="sample-posts"/><category term="formatting"/><category term="links"/><summary type="html"><![CDATA[a short philosophical discursion]]></summary></entry><entry><title type="html">On our ACL Best Paper Award Paper</title><link href="https://changelinglab.github.io/blog/2024/best_paper/" rel="alternate" type="text/html" title="On our ACL Best Paper Award Paper"/><published>2024-08-07T16:40:16+00:00</published><updated>2024-08-07T16:40:16+00:00</updated><id>https://changelinglab.github.io/blog/2024/best_paper</id><content type="html" xml:base="https://changelinglab.github.io/blog/2024/best_paper/"><![CDATA[<p>Yesterday, my student Liang (Leon) Lu won the Best Paper Award (Non-Publicized) at the 2024 Association for Computational Linguistics conference in Bangkok for his paper “Semisupervised Neural Proto-Language Reconstruction.” We are generally impressed by students who win this awards, but in Leon’s case their is double reason to be impressed. Not only is he an undergraduate student (just starting his third year of university), he has only submitted two papers to conferences. Both were accepted and the second (his first submission to a *ACL conference) was the subject of this best paper award. But what is the substance of this paper?</p> <p>If you are technical, you can go and read the paper for yourself. It is short and is, I think, fairly clearly written. If you are not technical but you have some training in historical linguistics, you will recognize some of the principal themes, even if you don’t follow the complete methodology or analysis. However, if you are neither technical nor trained in historical linguistics, but you still want to know what this paper was about, I will do me best to let you know.</p> <p>First, let us consider a table of words from the related languages Kachai, Huishu, and Ukhrul (members of the family of languages called Tangkhulic):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> </table> <p>Note that the ð sound is like the th in <em>this</em> and the ɐ sound is sort of like the u in cup.</p> <p>If you look at these words, you can see that there is, for example, a systematic relationship between the words for ‘bone‘ and those for ‘breast’. This extends to ‘grandchild’ as well, even though there is a somewhat unexpected consonant in Kachai (ð). What did the ancestors of these words look like in the shared ancestor of these languages? Is this lost in the mists of history?</p> <p>A group of 19th century linguists (of philologists, to use the terminology then current) called the Neogrammarians said you can know how these ancestral forms of words (protoforms) were pronounced by applying a methodology we now call the Comparative Method. Central to this method is the <strong>regularity principle</strong> which states that changes in pronunciation apply as general rules to which <strong>all</strong> words in a language are subject. This means that if you know the protoform for one of the columns in the table (these columns are what are known as “cognate sets”) you can derive all of the rows in that column deterministically—mechanically and unambiguously.</p> <p>Under these Neogrammarian assumptions, we could posit *ruk or *ru as reconstructions for ‘bone’. If we posit *ru, we must assert that there was a sound change in Kachai that changed u to ɐ and a sound change in Huishu that inserted k at the ends of words (perhaps after u). If we reconstruction *ruk, we have to assume that there was a sound change in both Kachai and Ukhrul that deletes k at the end of words (perhaps after u) and another sound change in Kachai that changes u to ɐ. The first option (*ru) ends up working better if we look at all of the cognate sets instead of just these four.</p> <p>By this logic, we get:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*?u</td> <td>*ru</td> <td>*nu</td> <td>*n?</td> </tr> </tbody> </table> <p>The reconstruction of ‘grandchild’ must end in u, but it must start with something other than r. Why? Because if it did start with r, there would be no way of explaining why, in Kachai, ‘grandchild’ starts with ð but ‘bone’ starts with r through the application of regular sound change. This would be an <strong>unconditioned split</strong>, something that the regularity principle rules out.</p> <p>Looking at the full collection of cognate sets, we would probably make the following reconstructions (or their formal equivalents):</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td>*nɨ</td> </tr> </tbody> </table> <p>where ɨ is a vowel that is half-way between i and u. These protoforms make sense based on the reflexes: they are similar in pronunciation to the reflexes and the reflexes can all be derived from them mechanically.</p> <p>There have been past efforts to build neural models (neural networks) that can perform this kind of reconstruction (including some from our lab), but they have two unfortunate properties:</p> <ol> <li>They only take the reflex-to-protoform mapping into account (not the protoform-to-reflex mapping).</li> <li>Training them (teaching them to generate reconstructions given sets of cognate reflexes) requires many cognate sets, each of which must be paired with a reconstruction.</li> </ol> <p>In actual reconstruction projects, as I know from first hand experience, the constraint in 2 is only satisfied when the most challenging and interesting work in reconstructing a protolanguage has already been done. What Leon discovered as part of this paper is that 2 is a consequence of 1—we are forced to do fully supervised training (a protoform for every cognate set) because we are not enforcing the regularity principle (not rejecting protoforms if—for example—identical protoforms are mapped to different reflex forms in a single language).</p> <p>To make things clearer, let’s return to our example. The older kind of fully-supervised reconstruction models is likely to produce the reconstructions below:</p> <table> <thead> <tr> <th>Gloss</th> <th>‘grandchild’</th> <th>‘bone’</th> <th>‘breast’</th> <th>‘laugh’</th> </tr> </thead> <tbody> <tr> <td>Kachai</td> <td>ðɐ</td> <td>rɐ</td> <td>nɐ</td> <td>ni</td> </tr> <tr> <td>Huishu</td> <td>ruk</td> <td>ruk</td> <td>nuk</td> <td>nuk</td> </tr> <tr> <td>Ukhrul</td> <td>ru</td> <td>ru</td> <td>nu</td> <td>nu</td> </tr> </tbody> <tbody> <tr> <td>Proto-Tangkhulic</td> <td>*du</td> <td>*ru</td> <td>*nu</td> <td><strong>*nu</strong></td> </tr> </tbody> </table> <p>This is because having a u in Ukhrul and a u in Huishu is generally a reliable cue for reconstructing *u in the protoform. However, this reconstruction cannot be right, following the regularity principle, because a single pronunciation in the protolanguage would be reflected as two different pronunciations in Kachai.</p> <p>Leon’s technical innovation was to design a neural network that can learn both to reconstruct protoforms based on reflexes (daughter-to-protoform) and to disfavor protoforms from which reflexes cannot be derived (proto-to-daughter). The D2P and P2D networks are joined together with a “bridge network” that allows both networks to be trained as a single network. The resulting type of neural network is similar in some ways to what is called a “variational autoencoder” but it differs in that the outputs of the D2P network are not real-valued vectors but strings of symbols (in the International Phonetic Alphabet).</p> <p>In training, the model can thus take advantage of cognate sets without a protoform, something that the earlier, fully supervised, models could not do.</p> <p>The implications of this development are striking. Given the same amount of labeled data (cognate sets with protoforms), our DPD models outperform the best fully supervised models as well as the best semisupervised models we could train. And careful statistical testing shows that the differences are as significant as they look at first glance.</p> <p>We think that this approach is very promising and looks forward to a day, not too far in the future, when neural models like this will be a tool in the belt of every historical linguist and will help shed light on the dark recesses of the human past.</p>]]></content><author><name></name></author><category term="sample-posts"/><category term="formatting"/><category term="links"/><summary type="html"><![CDATA[a short philosophical discursion]]></summary></entry><entry><title type="html">Is ACL an AI (or NLP or CL) Conference?</title><link href="https://changelinglab.github.io/blog/2024/cl_in_acl/" rel="alternate" type="text/html" title="Is ACL an AI (or NLP or CL) Conference?"/><published>2024-08-07T16:40:16+00:00</published><updated>2024-08-07T16:40:16+00:00</updated><id>https://changelinglab.github.io/blog/2024/cl_in_acl</id><content type="html" xml:base="https://changelinglab.github.io/blog/2024/cl_in_acl/"><![CDATA[<p><a href="/assets/img/acl_is_not_ai_conference.jpg"></a></p> <p>In the title of a controversial Presidential Address at ACL2024, Emily Bender proclaimed that “ACL is not an AI conference.“ I was not fortunate enough to be in Bangkok to hear the address, but I have read the slides and, since it concerns me personally, I want to write a short response.</p> <p>tl;dr Reinforcing disciplinary boundaries between CL, NLP, and ML makes all three disciplines poorer and less coherent. They <strong>all</strong> belong at ACL. As for “AI,” it is not a discipline but a marketing term and contrasting it with the big three is a category error.</p> <p>I am a Computational Linguist who is deeply embedded in the ACL community. I am not alone. People who try to paint ACL as an NLP conference only (e.g., Yoav Goldberg) are ignored the substantial number of CL scientists who participate in ACL in all capacities and the role that CL has always played in the *ACL organizations and conferences. Bender commits the same type of error when she tries to exclude or marginalize “AI,” by which I assume she means machine learning. This is problematic in a couple of respects:</p> <ol> <li><strong>AI is not a discipline, technology, community, or anything substantial at all—it is a marketing term.</strong> One might as coherently say that ACL is not a phlogiston conference as to say that it is not an “AI” conference. AI has referred to symbolic systems like the HPSG grammars for which Bender is well known, expert systems, behavior trees guiding video game characters, classical statistical machine learning, perceptrons, deep neural nets, language models, and so on. AI is just “computers looking smart so you’ll give us money” and not anything a conference could be about.</li> <li>If she means “machine learning” then, in a sense, she’s right—almost no one believes that ACL is a machine learning conference in the sense that ICML, ICLR, and NeurIPS are. However, <strong>to exclude work from the conference that is focused on ML techniques (which are thoroughly embedded in modern NLP and CL) would make the community vastly poorer.</strong> And there is no reason that ACL cannot be a CL conference, and NLP conference, and an ML conference. These fields intersect and reinforce each other and well all benefit from interacting (and even confronting) one another.</li> </ol> <p>I understand one of Bender’s points: many younger reviewers, even in linguistics-heavy tracks like Linguistic Theories and Cognitive Modeling and Phonology, Morphology, and Word Segmentation, will criticize papers for lacking novelty (really technical novelty) when they concentrate on answering a scientific question about language (or a language) rather than presenting a technical innovation. I’ve encountered this when writing metareviews as an AC and AE. I’ve also encountered it first hand. For example, I once received a very low review on a linguistics paper submitted to a *ACL because the ML techniques used were well-known (decision trees, SVMs, and generic LSTMs and CNNs). The reviewer, apparently not familiar with linguistic research, missed our point, which is that these tools resolved a theoretically significant question about the languages under investigation. (Ironically, another reviewer attacked us for ignoring linguistic theory because our findings did not accord with their theoretical preconceptions). In this case, as in many cases I’ve seen, an AC with a broader view of the field(s) stepped in and wrote a balanced and informed metareview. This is not to say that the system is perfect; only that overly strong statements about linguistics being pushed out of ACL by AI-intoxicated reviewers are not helpful.</p> <p>In fact, there is no reason for linguistics, as a field, to be at odds with ML. The animosity, I think, comes from the incompatibility of a certain <strong>kind</strong> of linguistics with a particular <strong>kind</strong> of machine learning researcher. Starting in the 1950s, North American linguistics was dominated by the generative school, which was built upon discrete symbolic representations governed by categorical rules and constraints and arrived at via a specific introspective methodology. This was compatible with (indeed, very much a part) of the first wave of “artificial intelligence” research. Head Driven Phrase Structure Grammar (on which Bender cut her teeth) grows out of this school (though it has a more computationally appealing formalism and a more empirically-oriented culture). But generative linguistics is not (and has never been) the only approached to the language sciences. Many linguists before, during, and after the heyday of generative grammar, have viewed language as grounded in stochastic patterns of usage and for these empirically-minded linguists, machine learning (whether classical or neural) is a natural, intuitive approach to language.</p> <p>The point of disagreement, really, is in what class of questions are interesting. Few linguists (even computational linguists) are really going be interested in knowledge distillation and few ML practitioners are really going to be interested in noncompositionality in Newari noun phrases. I would like to advance the radical proposition that it is okay for a professional organization and a conference to embrace people who are interested in different things. I would go further and say that we benefit from being in an organization with people who have different interests and backgrounds than we have. In the end, we all have language to tie us together, and we all have computing to tie us together.</p> <p>I sincerely believe that the name of the ACL should change. We should keep “ACL” but change the full name to “<strong>the Association for Computing and Language</strong>.” This matched better what the ACL is to me and sets the tenor for a community that embraces a spectrum of research interests and practices.</p>]]></content><author><name></name></author><category term="sample-posts"/><category term="formatting"/><category term="links"/><summary type="html"><![CDATA[Ruminations on Emily Bender's Presidential Address at ACL2024]]></summary></entry></feed>
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We are interested in phonetics, phonology, and morphology (whether diachronic or synchronic), emergent communication, and have a special concern for the use of language science to benefit people with disabilities.</p> <p>ChangeLing is lead by <a href="https://www.cs.cmu.edu/~dmortens/" rel="external nofollow noopener" target="_blank">David R. Mortensen</a>, an Assistant Research Professor in the Language Technologies Institute. It consists, additionally, of graduate students, former LTI students who still collaborate with David, and visitors.</p> <p>If you are interested in joining ChangeLing, please email David at <a href="mailto:dmortens@cs.cmu.edu">dmortens@cs.cmu.edu</a> with a CV and a description of what work you would like to do with us. Please take the following into account:</p> <ul> <li>We are only concerned with work that has some linguistic angle (either it uses linguistics or it is useful for linguists). Students who are concerned with machine learning for its own sake would be better served by another lab.</li> <li>We are interested in large language models, but only with respect to their language and linguistic reasoning capabilities. Our lab is not a good place to do general, engineering-focused or fundamental research on LLMs.</li> </ul> </div> <h2> <a href="/news/" style="color: inherit">news</a> </h2> <div class="news"> <div class="table-responsive"> <table class="table table-sm table-borderless"> <tr> <th scope="row" style="width: 20%">Aug 14, 2024</th> <td> Congratulations to Liang (Leon) Lu for winning the ACL2024 Best Paper Award (Non-Publicized) with his paper “Self-Supervised Neural Protolanguage Reconstruction” (joint work with Peirong Xie and David Mortensen). </td> </tr> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <img class="emoji" title=":sparkles:" alt=":sparkles:" src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png" height="20" width="20"> <strong>ChangeLing Lab is officially born!</strong> <img class="emoji" title=":sparkles:" alt=":sparkles:" src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png" height="20" width="20"> (though it has long existed in fact). </td> </tr> </table> </div> </div> <h2> <a href="/blog/" style="color: inherit">latest posts</a> </h2> <div class="news"> <div class="table-responsive"> <table class="table table-sm table-borderless"> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <a class="news-title" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </td> </tr> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <a class="news-title" href="/blog/2024/why-diachronic-linguistics/">Why does diachronic linguistics matter?</a> </td> </tr> </table> </div> </div> <h2> <a href="/publications/" style="color: inherit">selected publications</a> </h2> <div class="publications"> <ol class="bibliography"></ol> </div> <div class="social"> <div class="contact-icons"> <a href="mailto:%64%6D%6F%72%74%65%6E%73@%63%73.%63%6D%75.%65%64%75" title="email"><i class="fa-solid fa-envelope"></i></a> <a href="https://orcid.org/0000-0002-3927-6851" title="ORCID" rel="external nofollow noopener" target="_blank"><i class="ai ai-orcid"></i></a> <a href="https://scholar.google.com/citations?user=2iS5aeoAAAAJ&amp;hl" title="Google Scholar" rel="external nofollow noopener" target="_blank"><i class="ai ai-google-scholar"></i></a> <a href="https://www.semanticscholar.org/author/3407646" title="Semantic Scholar" rel="external nofollow noopener" target="_blank"><i class="ai ai-semantic-scholar"></i></a> <a href="https://github.com/changelinglab" title="GitHub" rel="external nofollow noopener" target="_blank"><i class="fa-brands fa-github"></i></a> <a href="https://twitter.com/dmort27" title="X" rel="external nofollow noopener" target="_blank"><i class="fa-brands fa-x-twitter"></i></a> <a href="/feed.xml" title="RSS Feed"><i class="fa-solid fa-square-rss"></i></a> </div> <div class="contact-note">I'm best reached by email or, if you are in the inner circle, by Slack. </div> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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We are interested in phonetics, phonology, and morphology (whether diachronic or synchronic), emergent communication, and have a special concern for the use of language science to benefit people with disabilities.</p> <p>ChangeLing is lead by <a href="https://www.cs.cmu.edu/~dmortens/" rel="external nofollow noopener" target="_blank">David R. Mortensen</a>, an Assistant Research Professor in the Language Technologies Institute. It consists, additionally, of graduate students, former LTI students who still collaborate with David, and visitors.</p> <p>If you are interested in joining ChangeLing, please email David at <a href="mailto:dmortens@cs.cmu.edu">dmortens@cs.cmu.edu</a> with a CV and a description of what work you would like to do with us. Please take the following into account:</p> <ul> <li>We are only concerned with work that has some linguistic angle (either it uses linguistics or it is useful for linguists). Students who are concerned with machine learning for its own sake would be better served by another lab.</li> <li>We are interested in large language models, but only with respect to their language and linguistic reasoning capabilities. Our lab is not a good place to do general, engineering-focused or fundamental research on LLMs.</li> </ul> </div> <h2> <a href="/news/" style="color: inherit">news</a> </h2> <div class="news"> <div class="table-responsive"> <table class="table table-sm table-borderless"> <tr> <th scope="row" style="width: 20%">Aug 14, 2024</th> <td> Congratulations to Liang (Leon) Lu for winning the ACL2024 Best Paper Award (Non-Publicized) with his paper “Self-Supervised Neural Protolanguage Reconstruction” (joint work with Peirong Xie and David Mortensen). </td> </tr> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <img class="emoji" title=":sparkles:" alt=":sparkles:" src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png" height="20" width="20"> <strong>ChangeLing Lab is officially born!</strong> <img class="emoji" title=":sparkles:" alt=":sparkles:" src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png" height="20" width="20"> (though it has long existed in fact). </td> </tr> </table> </div> </div> <h2> <a href="/blog/" style="color: inherit">latest posts</a> </h2> <div class="news"> <div class="table-responsive"> <table class="table table-sm table-borderless"> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <a class="news-title" href="/blog/2024/cl_in_acl/">Is ACL an AI (or NLP or CL) Conference?</a> </td> </tr> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <a class="news-title" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </td> </tr> <tr> <th scope="row" style="width: 20%">Aug 07, 2024</th> <td> <a class="news-title" href="/blog/2024/why-diachronic-linguistics/">Why does diachronic linguistics matter?</a> </td> </tr> </table> </div> </div> <h2> <a href="/publications/" style="color: inherit">selected publications</a> </h2> <div class="publications"> <ol class="bibliography"></ol> </div> <div class="social"> <div class="contact-icons"> <a href="mailto:%64%6D%6F%72%74%65%6E%73@%63%73.%63%6D%75.%65%64%75" title="email"><i class="fa-solid fa-envelope"></i></a> <a href="https://orcid.org/0000-0002-3927-6851" title="ORCID" rel="external nofollow noopener" target="_blank"><i class="ai ai-orcid"></i></a> <a href="https://scholar.google.com/citations?user=2iS5aeoAAAAJ&amp;hl" title="Google Scholar" rel="external nofollow noopener" target="_blank"><i class="ai ai-google-scholar"></i></a> <a href="https://www.semanticscholar.org/author/3407646" title="Semantic Scholar" rel="external nofollow noopener" target="_blank"><i class="ai ai-semantic-scholar"></i></a> <a href="https://github.com/changelinglab" title="GitHub" rel="external nofollow noopener" target="_blank"><i class="fa-brands fa-github"></i></a> <a href="https://twitter.com/dmort27" title="X" rel="external nofollow noopener" target="_blank"><i class="fa-brands fa-x-twitter"></i></a> <a href="/feed.xml" title="RSS Feed"><i class="fa-solid fa-square-rss"></i></a> </div> <div class="contact-note">I'm best reached by email or, if you are in the inner circle, by Slack. </div> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Announcement_2_best_paper | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="The CMU Language Change and Empirical Linguistics Lab "> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/news/announcement_2_best_paper/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Announcement_2_best_paper</h1> <p class="post-meta"> Created in August 14, 2024 </p> <p class="post-tags"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </p> </header> <article class="post-content"> <div id="markdown-content"> <p>Congratulations to Liang (Leon) Lu for winning the ACL2024 Best Paper Award (Non-Publicized) with his paper “Self-Supervised Neural Protolanguage Reconstruction” (joint work with Peirong Xie and David Mortensen).</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/why-diachronic-linguistics/">Why does diachronic linguistics matter?</a> </li> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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August 14, 2024 </p> <p class="post-tags"> <i class="fa-solid fa-calendar fa-sm"></i> 2024 </p> </header> <article class="post-content"> <div id="markdown-content"> <p>Congratulations to Liang (Leon) Lu for winning the ACL2024 Best Paper Award (Non-Publicized) with his paper “Self-Supervised Neural Protolanguage Reconstruction” (joint work with Peirong Xie and David Mortensen).</p> </div> </article> <br> <hr> <br> <ul class="list-disc pl-8"></ul> <h2 class="text-3xl font-semibold mb-4 mt-12">Enjoy Reading This Article?</h2> <p class="mb-2">Here are some more articles you might like to read next:</p> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/cl_in_acl/">Is ACL an AI (or NLP or CL) Conference?</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold hover:text-pink-800" href="/blog/2024/best_paper/">On our ACL Best Paper Award Paper</a> </li> <li class="my-2"> <a class="text-pink-700 underline font-semibold 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> people | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Members and retroactive alumni of ChangLing Lab"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/people/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item active"> <a class="nav-link" href="/people/">people <span class="sr-only">(current)</span> </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">people</h1> <p class="post-description">Members and retroactive alumni of ChangLing Lab</p> </header> <article> <div class="post"> <article> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/david-mortensen-480.webp 480w,/assets/img/david-mortensen-800.webp 800w,/assets/img/david-mortensen-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/david-mortensen.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="david-mortensen.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://cs.cmu.edu/~dmortens/" rel="external nofollow noopener" target="_blank">David R. Mortensen</a></strong></p> <p><strong>Assistant Research Professor</strong></p> <p>GHC 5407</p> <p>5000 Forbes Ave</p> <p>Pittsburgh, PA 15213</p> </div> </div> <div class="clearfix"> <p>David R. Mortensen is a computational linguist specializing in phonology, morphology, and language change and is Assistant Research Professor in the Language Technologies Institute at Carnegie Mellon University. He is the head of ChangeLing Lab.</p> </div> <hr> <div class="profile float-right"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/brendon-boldt-480.webp 480w,/assets/img/brendon-boldt-800.webp 800w,/assets/img/brendon-boldt-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/brendon-boldt.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="brendon-boldt.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://brendonjboldt.xyz/" rel="external nofollow noopener" target="_blank">Brendon Boldt</a></strong></p> <p><strong>PhD Student</strong></p> <p>office number</p> <p>5000 Forbes Ave</p> <p>Pittsburgh, PA 15213</p> </div> </div> <div class="clearfix"> <p>Brendon Boldt is an 3rd year PhD student in ChangLing Lab. He works primarily on emergent language/emergent communication and is about to propose a thesis about it.</p> </div> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/kwanghee-choi-480.webp 480w,/assets/img/kwanghee-choi-800.webp 800w,/assets/img/kwanghee-choi-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/kwanghee-choi.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="kwanghee-choi.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://kwangheechoi.com/" rel="external nofollow noopener" target="_blank">Kwanghee Choi</a></strong></p> <p><strong>Master's Student (joint with WAVLab)</strong></p> </div> </div> <div class="clearfix"> <p>Kwanghee Choi is a second-year Master’s student in the LTI and is a member of both <a href="https://www.wavlab.org/" rel="external nofollow noopener" target="_blank">WAVLab</a> and ChangeLing Lab. He focuses on the interpretability of self-supervised speech models from the viewpoint of linguistics and information theory, with downstream applications such as discrete ASR or dysarthric speech assessment.</p> </div> <hr> <div class="profile float-right"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/liang-lu-480.webp 480w,/assets/img/liang-lu-800.webp 800w,/assets/img/liang-lu-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/liang-lu.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="liang-lu.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong>Liang (Leon) Lu</strong></p> <p><strong>Undergraduate Student</strong></p> </div> </div> <div class="clearfix"> <p>Leon (or Liang) Lu is an undergraduate in computer science at CMU. He has diverse interests. As part of ChangeLing Lab, he has worked on automating linguists’ “comparative method” for reconstructing proto-languages given sets of cognate reflexes.</p> </div> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/kalvin-chang-480.webp 480w,/assets/img/kalvin-chang-800.webp 800w,/assets/img/kalvin-chang-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/kalvin-chang.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="kalvin-chang.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong>Kalvin Chang</strong></p> <p><strong>Visitor (joint with WAVLab)</strong></p> </div> </div> <div class="clearfix"> <p>Kalvin Chang worked with David while he was an undergraduate and Masters student at CMU. After some time at Amazon, he has joined <a href="https://www.wavlab.org/" rel="external nofollow noopener" target="_blank">WAVLab</a> and ChangeLing Lab as a vistor during Fall 2024. Kalvin is especially interested in speech technologies for related varieties of languages (sometimes called “dialects”).</p> </div> <hr> <div class="profile float-right"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/eunjung-yeo-480.webp 480w,/assets/img/eunjung-yeo-800.webp 800w,/assets/img/eunjung-yeo-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/eunjung-yeo.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="eunjung-yeo.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://eunjung31.github.io/" rel="external nofollow noopener" target="_blank">Eunjung Yeo</a></strong></p> <p><strong>Visitor</strong></p> </div> </div> <div class="clearfix"> <p>Eunjung Yeo recently completed her Ph.D. in Linguistics at Seoul National University and has joined the ChangeLing Lab as a visitor in 2024. Her research has focused on the application of technologies for atypical speech, including dysarthric and nonnative speech, from the perspectives of phonetics and phonology.</p> </div> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/haeji-jung-480.webp 480w,/assets/img/haeji-jung-800.webp 800w,/assets/img/haeji-jung-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/haeji-jung.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="haeji-jung.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong>Haeji Jung</strong></p> <p><strong>Visitor</strong></p> </div> </div> <div class="clearfix"> <p>Haeji Jung earned her Master’s degree in Computer Science and Engineering from Korea University and is visiting ChangeLing Lab during 2024-2025. She has been working on representation learning and is currently interested in leveraging phonological representations for multilingual language modeling and other NLP applications.</p> </div> </article> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. Hosted by <a href="https://pages.github.com/" target="_blank" rel="external nofollow noopener">GitHub Pages</a>. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> people | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Members and retroactive alumni of ChangLing Lab"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/people/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item active"> <a class="nav-link" href="/people/">people <span class="sr-only">(current)</span> </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">people</h1> <p class="post-description">Members and retroactive alumni of ChangLing Lab</p> </header> <article> <div class="post"> <article> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/david-mortensen-480.webp 480w,/assets/img/david-mortensen-800.webp 800w,/assets/img/david-mortensen-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/david-mortensen.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="david-mortensen.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://cs.cmu.edu/~dmortens/" rel="external nofollow noopener" target="_blank">David R. Mortensen</a></strong></p> <p><strong>Assistant Research Professor</strong></p> <p>GHC 5407</p> <p>5000 Forbes Ave</p> <p>Pittsburgh, PA 15213</p> </div> </div> <div class="clearfix"> <p>David R. Mortensen is a computational linguist specializing in phonology, morphology, and language change and is Assistant Research Professor in the Language Technologies Institute at Carnegie Mellon University. He is the head of ChangeLing Lab.</p> </div> <hr> <div class="profile float-right"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/brendon-boldt-480.webp 480w,/assets/img/brendon-boldt-800.webp 800w,/assets/img/brendon-boldt-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/brendon-boldt.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="brendon-boldt.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://brendonjboldt.xyz/" rel="external nofollow noopener" target="_blank">Brendon Boldt</a></strong></p> <p><strong>PhD Student</strong></p> <p>office number</p> <p>5000 Forbes Ave</p> <p>Pittsburgh, PA 15213</p> </div> </div> <div class="clearfix"> <p>Brendon Boldt is an 3rd year PhD student in ChangLing Lab. He works primarily on emergent language/emergent communication and is about to propose a thesis about it.</p> </div> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/kwanghee-choi-480.webp 480w,/assets/img/kwanghee-choi-800.webp 800w,/assets/img/kwanghee-choi-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/kwanghee-choi.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="kwanghee-choi.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://kwangheechoi.com/" rel="external nofollow noopener" target="_blank">Kwanghee Choi</a></strong></p> <p><strong>Master's Student (joint with WAVLab)</strong></p> </div> </div> <div class="clearfix"> <p>Kwanghee Choi is a second-year Master’s student in the LTI and is a member of both <a href="https://www.wavlab.org/" rel="external nofollow noopener" target="_blank">WAVLab</a> and ChangeLing Lab. He focuses on the interpretability of self-supervised speech models from the viewpoint of linguistics and information theory, with downstream applications such as discrete ASR or dysarthric speech assessment.</p> </div> <hr> <div class="profile float-right"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/liang-lu-480.webp 480w,/assets/img/liang-lu-800.webp 800w,/assets/img/liang-lu-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/liang-lu.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="liang-lu.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong>Liang (Leon) Lu</strong></p> <p><strong>Undergraduate Student</strong></p> </div> </div> <div class="clearfix"> <p>Leon (or Liang) Lu is an undergraduate in computer science at CMU. He has diverse interests. As part of ChangeLing Lab, he has worked on automating linguists’ “comparative method” for reconstructing proto-languages given sets of cognate reflexes.</p> </div> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/kalvin-chang-480.webp 480w,/assets/img/kalvin-chang-800.webp 800w,/assets/img/kalvin-chang-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/kalvin-chang.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="kalvin-chang.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong>Kalvin Chang</strong></p> <p><strong>Visitor (joint with WAVLab)</strong></p> </div> </div> <div class="clearfix"> <p>Kalvin Chang worked with David while he was an undergraduate and Masters student at CMU. After some time at Amazon, he has joined <a href="https://www.wavlab.org/" rel="external nofollow noopener" target="_blank">WAVLab</a> and ChangeLing Lab as a vistor during Fall 2024. Kalvin is especially interested in speech technologies for related varieties of languages (sometimes called “dialects”).</p> </div> <hr> <div class="profile float-right"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/eunjung-yeo-480.webp 480w,/assets/img/eunjung-yeo-800.webp 800w,/assets/img/eunjung-yeo-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/eunjung-yeo.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="eunjung-yeo.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong><a href="https://eunjung31.github.io/" rel="external nofollow noopener" target="_blank">Eunjung Yeo</a></strong></p> <p><strong>Visitor</strong></p> </div> </div> <div class="clearfix"> <p>Eunjung Yeo recently completed her Ph.D. in Linguistics at Seoul National University and has joined the ChangeLing Lab as a visitor in 2024. Her research has focused on the application of technologies for atypical speech, including dysarthric and nonnative speech, from the perspectives of phonetics and phonology.</p> </div> <hr> <div class="profile float-left"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/haeji-jung-480.webp 480w,/assets/img/haeji-jung-800.webp 800w,/assets/img/haeji-jung-1400.webp 1400w," sizes="(min-width: 930px) 270.0px, (min-width: 576px) 30vw, 95vw" type="image/webp"> <img src="/assets/img/haeji-jung.jpg" class="img-fluid z-depth-1 rounded-circle" width="100%" height="auto" alt="haeji-jung.jpg" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </source></picture> </figure> <div class="more-info"> <p><strong>Haeji Jung</strong></p> <p><strong>Visitor</strong></p> </div> </div> <div class="clearfix"> <p>Haeji Jung earned her Master’s degree in Computer Science and Engineering from Korea University and is visiting ChangeLing Lab during 2024-2025. She has been working on representation learning and is currently interested in leveraging phonological representations for multilingual language modeling and other NLP applications.</p> </div> </article> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. Hosted by <a href="https://pages.github.com/" target="_blank" rel="external nofollow noopener">GitHub Pages</a>. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Automating Comparative Reconstruction | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Work on developing models that reconstruct protolanguages based on collections of cognate sets"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/1_automating/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Automating Comparative Reconstruction</h1> <p class="post-description">Work on developing models that reconstruct protolanguages based on collections of cognate sets</p> </header> <article> <p>In the 19th century, European philologists made a discovery that would change the direction of the human sciences: they discovered that languages change in systematic ways and that, by leveraging these systematic patterns, it was possible to reproducibly reconstruct ancestors of families of languages (proto-languages) even when no record of those languages survived. This technique, called the comparative method, provided an unprecedented window into the human past—its cultures, its migrations, and its encounters between populations.</p> <p>The assumption that historical changes in pronunciation (“sound changes”) are regular, known as ‘the regularity principle’ or ‘the Neogrammarian hypothesis’, is fundamental to the comparative method. As the 19th century Neogrammarians Hermann Osthoff and Karl Brugmann put it:</p> <blockquote> <p>Every sound change, in so far as it proceeds mechanically, is completed in accordance with laws admitting of no exceptions; i.e. the direction in which the change takes place is always the same for all members of a language community, apart from the case of dialect division, and all words in which the sound subject to change occurs in the same conditions are affected by the change without exception (<em>Morphologische Untersuchungen auf dem Gebiete der indogermanischen Sprachen i</em>).</p> </blockquote> <p>The comparative method, however, is challenging for humans to apply. This is true largely because it involves dealing with large volumes of data and modeling numerous interactions between competing patterns. One must balance the need for phonetic similarity between reconstructed words and their descendants (reflexes) with the need to be able to deterministically derive reflexes from reconstructed words with a single set of sound changes. It imposes a heavy cognitive load. For this reason, researchers have long aspired to implement the comparative method computationally.</p> <p>In this research, we build upon past research in this area.</p> <ul> <li>In <a class="citation" href="#chang2022wikihan">(Chang et al., 2022)</a>, we propose a new resource for Chinese historical phonology (including Middle Chinese and modern Chinese varieties). This data is foundational to our later papers.</li> <li>In <a class="citation" href="#kim2023transformed">(Kim et al., 2023)</a>, we show that Transformer-based models can perform better than RNN (e.g., GRU) based models for supervised protoform reconstruction.</li> <li>In <a class="citation" href="#lu-etal-2024-improved">(Lu et al., 2024)</a>, we further improve automatic comparative reconstruction by using reflex prediction to perform reranking on the beam search results from protoform prediction, emulating the methodology of practicing historical linguists.</li> <li>In <a class="citation" href="#cui2024neuralprotolanguagereconstruction">(Cui et al., 2024)</a>, we explored VAEs for supervised comparative reconstruction.</li> <li>Finally. in <a class="citation" href="#lu2024semisupervisedneuralprotolanguagereconstruction">(Lu et al., 2024)</a>, we showed that it is possible to achieve strong performance on the protoform reconstruction task using only a fraction of the number of labeled data by using the Proto-Daughter-Proto architecture, an end-to-end architecture that favors protoforms that can be derived from cognate sets and from which cognate sets can be derived.</li> </ul> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu-etal-2024-improved" class="col-sm-8"> <div class="title">Improved Neural Protoform Reconstruction via Reflex Prediction</div> <div class="author"> Liang Lu, Jingzhi Wang, and David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protolanguage reconstruction is central to historical linguistics. The comparative method, one of the most influential theoretical and methodological frameworks in the history of the language sciences, allows linguists to infer protoforms (reconstructed ancestral words) from their reflexes (related modern words) based on the assumption of regular sound change. Not surprisingly, numerous computational linguists have attempted to operationalize comparative reconstruction through various computational models, the most successful of which have been supervised encoder-decoder models, which treat the problem of predicting protoforms given sets of reflexes as a sequence-to-sequence problem. We argue that this framework ignores one of the most important aspects of the comparative method: not only should protoforms be inferable from cognate sets (sets of related reflexes) but the reflexes should also be inferable from the protoforms. Leveraging another line of research—reflex prediction—we propose a system in which candidate protoforms from a reconstruction model are reranked by a reflex prediction model. We show that this more complete implementation of the comparative method allows us to surpass state-of-the-art protoform reconstruction methods on three of four Chinese and Romance datasets.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="cui2024neuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Neural Proto-Language Reconstruction</div> <div class="author"> Chenxuan Cui, Ying Chen, Qinxin Wang, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> May 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu2024semisupervisedneuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Semisupervised Neural Proto-Language Reconstruction</div> <div class="author"> Liang Lu, Peirong Xie, and David R. Mortensen </div> <div class="periodical"> May 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2023</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="kim2023transformed" class="col-sm-8"> <div class="title">Transformed Protoform Reconstruction</div> <div class="author"> Young Min Kim, Kalvin Chang, Chenxuan Cui, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protoform reconstruction is the task of inferring what morphemes or words appeared like in the ancestral languages of a set of daughter languages. Meloni et al (2021) achieved the state-of-the-art on Latin protoform reconstruction with an RNN-based encoder-decoder with attention model. We update their model with the state-of-the-art seq2seq model: the Transformer. Our model outperforms their model on a suite of different metrics on two different datasets: their Romance data of 8,000 cognates spanning 5 languages and a Chinese dataset (Hou 2004) of 800+ cognates spanning 39 varieties. We also probe our model for potential phylogenetic signal contained in the model. Our code is publicly available at \urlhttps://github.com/cmu-llab/acl-2023.</p> </div> </div> </div> </li></ol> <h2 class="bibliography">2022</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chang2022wikihan" class="col-sm-8"> <div class="title">WikiHan: A New Comparative Dataset for Chinese Languages</div> <div class="author"> Kalvin Chang, Chenxuan Cui, Youngmin Kim, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Automating Comparative Reconstruction | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Work on developing models that reconstruct protolanguages based on collections of cognate sets"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/1_automating/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Automating Comparative Reconstruction</h1> <p class="post-description">Work on developing models that reconstruct protolanguages based on collections of cognate sets</p> </header> <article> <p>In the 19th century, European philologists made a discovery that would change the direction of the human sciences: they discovered that languages change in systematic ways and that, by leveraging these systematic patterns, it was possible to reproducibly reconstruct ancestors of families of languages (proto-languages) even when no record of those languages survived. This technique, called the comparative method, provided an unprecedented window into the human past—its cultures, its migrations, and its encounters between populations.</p> <p>The assumption that historical changes in pronunciation (“sound changes”) are regular, known as ‘the regularity principle’ or ‘the Neogrammarian hypothesis’, is fundamental to the comparative method. As the 19th century Neogrammarians Hermann Osthoff and Karl Brugmann put it:</p> <blockquote> <p>Every sound change, in so far as it proceeds mechanically, is completed in accordance with laws admitting of no exceptions; i.e. the direction in which the change takes place is always the same for all members of a language community, apart from the case of dialect division, and all words in which the sound subject to change occurs in the same conditions are affected by the change without exception (<em>Morphologische Untersuchungen auf dem Gebiete der indogermanischen Sprachen i</em>).</p> </blockquote> <p>The comparative method, however, is challenging for humans to apply. This is true largely because it involves dealing with large volumes of data and modeling numerous interactions between competing patterns. One must balance the need for phonetic similarity between reconstructed words and their descendants (reflexes) with the need to be able to deterministically derive reflexes from reconstructed words with a single set of sound changes. It imposes a heavy cognitive load. For this reason, researchers have long aspired to implement the comparative method computationally.</p> <p>In this research, we build upon past research in this area.</p> <ul> <li>In <a class="citation" href="#chang2022wikihan">(Chang et al., 2022)</a>, we propose a new resource for Chinese historical phonology (including Middle Chinese and modern Chinese varieties). This data is foundational to our later papers.</li> <li>In <a class="citation" href="#kim2023transformed">(Kim et al., 2023)</a>, we show that Transformer-based models can perform better than RNN (e.g., GRU) based models for supervised protoform reconstruction.</li> <li>In <a class="citation" href="#lu-etal-2024-improved">(Lu et al., 2024)</a>, we further improve automatic comparative reconstruction by using reflex prediction to perform reranking on the beam search results from protoform prediction, emulating the methodology of practicing historical linguists.</li> <li>In <a class="citation" href="#cui2024neuralprotolanguagereconstruction">(Cui et al., 2024)</a>, we explored VAEs for supervised comparative reconstruction.</li> <li>Finally. in <a class="citation" href="#lu2024semisupervisedneuralprotolanguagereconstruction">(Lu et al., 2024)</a>, we showed that it is possible to achieve strong performance on the protoform reconstruction task using only a fraction of the number of labeled data by using the Proto-Daughter-Proto architecture, an end-to-end architecture that favors protoforms that can be derived from cognate sets and from which cognate sets can be derived.</li> </ul> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu-etal-2024-improved" class="col-sm-8"> <div class="title">Improved Neural Protoform Reconstruction via Reflex Prediction</div> <div class="author"> Liang Lu, Jingzhi Wang, and David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protolanguage reconstruction is central to historical linguistics. The comparative method, one of the most influential theoretical and methodological frameworks in the history of the language sciences, allows linguists to infer protoforms (reconstructed ancestral words) from their reflexes (related modern words) based on the assumption of regular sound change. Not surprisingly, numerous computational linguists have attempted to operationalize comparative reconstruction through various computational models, the most successful of which have been supervised encoder-decoder models, which treat the problem of predicting protoforms given sets of reflexes as a sequence-to-sequence problem. We argue that this framework ignores one of the most important aspects of the comparative method: not only should protoforms be inferable from cognate sets (sets of related reflexes) but the reflexes should also be inferable from the protoforms. Leveraging another line of research—reflex prediction—we propose a system in which candidate protoforms from a reconstruction model are reranked by a reflex prediction model. We show that this more complete implementation of the comparative method allows us to surpass state-of-the-art protoform reconstruction methods on three of four Chinese and Romance datasets.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="cui2024neuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Neural Proto-Language Reconstruction</div> <div class="author"> Chenxuan Cui, Ying Chen, Qinxin Wang, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> May 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu2024semisupervisedneuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Semisupervised Neural Proto-Language Reconstruction</div> <div class="author"> Liang Lu, Peirong Xie, and David R. Mortensen </div> <div class="periodical"> May 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2023</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="kim2023transformed" class="col-sm-8"> <div class="title">Transformed Protoform Reconstruction</div> <div class="author"> Young Min Kim, Kalvin Chang, Chenxuan Cui, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protoform reconstruction is the task of inferring what morphemes or words appeared like in the ancestral languages of a set of daughter languages. Meloni et al (2021) achieved the state-of-the-art on Latin protoform reconstruction with an RNN-based encoder-decoder with attention model. We update their model with the state-of-the-art seq2seq model: the Transformer. Our model outperforms their model on a suite of different metrics on two different datasets: their Romance data of 8,000 cognates spanning 5 languages and a Chinese dataset (Hou 2004) of 800+ cognates spanning 39 varieties. We also probe our model for potential phylogenetic signal contained in the model. Our code is publicly available at \urlhttps://github.com/cmu-llab/acl-2023.</p> </div> </div> </div> </li></ol> <h2 class="bibliography">2022</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chang2022wikihan" class="col-sm-8"> <div class="title">WikiHan: A New Comparative Dataset for Chinese Languages</div> <div class="author"> Kalvin Chang, Chenxuan Cui, Youngmin Kim, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In COLING 2022</em>, Jul 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. Hosted by <a href="https://pages.github.com/" target="_blank" rel="external nofollow noopener">GitHub Pages</a>. 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diff --git a/projects/2_codegen/index.html b/projects/2_codegen/index.html
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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Historical Linguistics as Code Generation | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Modeling phonological reconstruction as a code generation problem using LLMs"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/2_codegen/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Historical Linguistics as Code Generation</h1> <p class="post-description">Modeling phonological reconstruction as a code generation problem using LLMs</p> </header> <article> <p>Since the Neogrammarians, when linguists write the phonological histories of languages, they essentially write programs (that convert protoforms into reflexes). 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Emergent Language Corpus Collection | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Building a collection of corpora from emergent communication systems"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/3_elcc/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Emergent Language Corpus Collection</h1> <p class="post-description">Building a collection of corpora from emergent communication systems</p> </header> <article> <p>We introduce the Emergent Language Corpus Collection (ELCC): a collection of corpora collected from open source implementations of emergent communication systems across the literature. These systems include a variety of signalling game environments as well as more complex tasks like a social deduction game and embodied navigation. Each corpus is annotated with metadata describing the characteristics of the source system as well as a suite of analyses of the corpus (e.g., size, entropy, average message length). Currently, research studying emergent languages requires directly running different systems which takes time away from actual analyses of such languages, limits the variety of languages that are studied, and presents a barrier to entry for researchers without a background in deep learning. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Emergent Language Corpus Collection | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Building a collection of corpora from emergent communication systems"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/3_elcc/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Emergent Language Corpus Collection</h1> <p class="post-description">Building a collection of corpora from emergent communication systems</p> </header> <article> <p>We introduce the Emergent Language Corpus Collection (ELCC): a collection of corpora collected from open source implementations of emergent communication systems across the literature. These systems include a variety of signalling game environments as well as more complex tasks like a social deduction game and embodied navigation. Each corpus is annotated with metadata describing the characteristics of the source system as well as a suite of analyses of the corpus (e.g., size, entropy, average message length). Currently, research studying emergent languages requires directly running different systems which takes time away from actual analyses of such languages, limits the variety of languages that are studied, and presents a barrier to entry for researchers without a background in deep learning. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> WugGPT | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Evaluating the morphological capabilities of Large Language Models"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/4_wuggpt/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">WugGPT</h1> <p class="post-description">Evaluating the morphological capabilities of Large Language Models</p> </header> <article> <p>The project, about testing the linguistics capabilities of large language models, has resulted in a couple of papers, with more to come:</p> <ul> <li><a class="citation" href="#weissweiler2023counting">(Weissweiler et al., 2023)</a></li> <li><a class="citation" href="#mortensen-etal-2024-verbing">(Mortensen et al., 2024)</a></li> </ul> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen-etal-2024-verbing" class="col-sm-8"> <div class="title">Verbing Weirds Language (Models): Evaluation of English Zero-Derivation in Five LLMs</div> <div class="author"> David R. Mortensen, Valentina Izrailevitch, Yunze Xiao, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Hinrich Schütze, Leonie Weissweiler' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Lexical-syntactic flexibility, in the form of conversion (or zero-derivation) is a hallmark of English morphology. In conversion, a word with one part of speech is placed in a non-prototypical context, where it is coerced to behave as if it had a different part of speech. However, while this process affects a large part of the English lexicon, little work has been done to establish the degree to which language models capture this type of generalization. This paper reports the first study on the behavior of large language models with reference to conversion. We design a task for testing lexical-syntactic flexibility—the degree to which models can generalize over words in a construction with a non-prototypical part of speech. This task is situated within a natural language inference paradigm. We test the abilities of five language models—two proprietary models (GPT-3.5 and GPT-4), three open source model (Mistral 7B, Falcon 40B, and Llama 2 70B). We find that GPT-4 performs best on the task, followed by GPT-3.5, but that the open source language models are also able to perform it and that the 7-billion parameter Mistral displays as little difference between its baseline performance on the natural language inference task and the non-prototypical syntactic category task, as the massive GPT-4.</p> </div> </div> </div> </li></ol> <h2 class="bibliography">2023</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="weissweiler2023counting" class="col-sm-8"> <div class="title">Counting the Bugs in ChatGPT’s Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model</div> <div class="author"> Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, and <span class="more-authors" title="click to view 10 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '10 more authors' ? 'Anna Cai, Ritam Dutt, Amey Hengle, Anubha Kabra, Atharva Kulkarni, Abhishek Vijayakumar, Haofei Yu, Hinrich Schuetze, Kemal Oflazer, David Mortensen' : '10 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">10 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relatively few systematic inquiries into the linguistic capabilities of the latest generation of LLMs, and those studies that do exist (i) ignore the remarkable ability of humans to generalize, (ii) focus only on English, and (iii) investigate syntax or semantics and overlook other capabilities that lie at the heart of human language, like morphology. Here, we close these gaps by conducting the first rigorous analysis of the morphological capabilities of ChatGPT in four typologically varied languages (specifically, English, German, Tamil, and Turkish). We apply a version of Berko’s (1958) wug test to ChatGPT, using novel, uncontaminated datasets for the four examined languages. We find that ChatGPT massively underperforms purpose-built systems, particularly in English. Overall, our results—through the lens of morphology—cast a new light on the linguistic capabilities of ChatGPT, suggesting that claims of human-like language skills are premature and misleading.</p> </div> </div> </div> </li></ol> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. Hosted by <a href="https://pages.github.com/" target="_blank" rel="external nofollow noopener">GitHub Pages</a>. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> WugGPT | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Evaluating the morphological capabilities of Large Language Models"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/4_wuggpt/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">WugGPT</h1> <p class="post-description">Evaluating the morphological capabilities of Large Language Models</p> </header> <article> <p>The project, about testing the linguistics capabilities of large language models, has resulted in a couple of papers, with more to come:</p> <ul> <li><a class="citation" href="#weissweiler2023counting">(Weissweiler et al., 2023)</a></li> <li><a class="citation" href="#mortensen-etal-2024-verbing">(Mortensen et al., 2024)</a></li> </ul> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen-etal-2024-verbing" class="col-sm-8"> <div class="title">Verbing Weirds Language (Models): Evaluation of English Zero-Derivation in Five LLMs</div> <div class="author"> David R. Mortensen, Valentina Izrailevitch, Yunze Xiao, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Hinrich Schütze, Leonie Weissweiler' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Lexical-syntactic flexibility, in the form of conversion (or zero-derivation) is a hallmark of English morphology. In conversion, a word with one part of speech is placed in a non-prototypical context, where it is coerced to behave as if it had a different part of speech. However, while this process affects a large part of the English lexicon, little work has been done to establish the degree to which language models capture this type of generalization. This paper reports the first study on the behavior of large language models with reference to conversion. We design a task for testing lexical-syntactic flexibility—the degree to which models can generalize over words in a construction with a non-prototypical part of speech. This task is situated within a natural language inference paradigm. We test the abilities of five language models—two proprietary models (GPT-3.5 and GPT-4), three open source model (Mistral 7B, Falcon 40B, and Llama 2 70B). We find that GPT-4 performs best on the task, followed by GPT-3.5, but that the open source language models are also able to perform it and that the 7-billion parameter Mistral displays as little difference between its baseline performance on the natural language inference task and the non-prototypical syntactic category task, as the massive GPT-4.</p> </div> </div> </div> </li></ol> <h2 class="bibliography">2023</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="weissweiler2023counting" class="col-sm-8"> <div class="title">Counting the Bugs in ChatGPT’s Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model</div> <div class="author"> Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, and <span class="more-authors" title="click to view 10 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '10 more authors' ? 'Anna Cai, Ritam Dutt, Amey Hengle, Anubha Kabra, Atharva Kulkarni, Abhishek Vijayakumar, Haofei Yu, Hinrich Schuetze, Kemal Oflazer, David Mortensen' : '10 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">10 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relatively few systematic inquiries into the linguistic capabilities of the latest generation of LLMs, and those studies that do exist (i) ignore the remarkable ability of humans to generalize, (ii) focus only on English, and (iii) investigate syntax or semantics and overlook other capabilities that lie at the heart of human language, like morphology. Here, we close these gaps by conducting the first rigorous analysis of the morphological capabilities of ChatGPT in four typologically varied languages (specifically, English, German, Tamil, and Turkish). We apply a version of Berko’s (1958) wug test to ChatGPT, using novel, uncontaminated datasets for the four examined languages. We find that ChatGPT massively underperforms purpose-built systems, particularly in English. Overall, our results—through the lens of morphology—cast a new light on the linguistic capabilities of ChatGPT, suggesting that claims of human-like language skills are premature and misleading.</p> </div> </div> </div> </li></ol> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. Hosted by <a href="https://pages.github.com/" target="_blank" rel="external nofollow noopener">GitHub Pages</a>. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> XferBench | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Evaluating Emergent Communication Systems with Downstream Tasks"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/5_xferbench/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">XferBench</h1> <p class="post-description">Evaluating Emergent Communication Systems with Downstream Tasks</p> </header> <article> <p>So far, the project has produced one paper <a class="citation" href="#boldt-mortensen-2024-xferbench">(Boldt &amp; Mortensen, 2024)</a>:</p> <blockquote> <p>In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the “quality” of an emergent language as its similarity to human language within a deep learning framework. We measure this by using the emergent language as pretraining data for a downstream NLP tasks in human language—the better the downstream performance, the better the emergent language. We implement this benchmark as an easy-to-use Python package that only requires a text file of utterances from the emergent language to be evaluated. Finally, we empirically test the benchmark’s validity using human, synthetic, and emergent language baselines.</p> </blockquote> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="boldt-mortensen-2024-xferbench" class="col-sm-8"> <div class="title">XferBench: a Data-Driven Benchmark for Emergent Language</div> <div class="author"> Brendon Boldt, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</em>, Jun 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the “quality” of an emergent language as its similarity to human language within a deep learning framework. We measure this by using the emergent language as pretraining data for a downstream NLP tasks in human language—the better the downstream performance, the better the emergent language. We implement this benchmark as an easy-to-use Python package that only requires a text file of utterances from the emergent language to be evaluated. Finally, we empirically test the benchmark’s validity using human, synthetic, and emergent language baselines.</p> </div> </div> </div> </li></ol> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> XferBench | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Evaluating Emergent Communication Systems with Downstream Tasks"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/5_xferbench/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">XferBench</h1> <p class="post-description">Evaluating Emergent Communication Systems with Downstream Tasks</p> </header> <article> <p>So far, the project has produced one paper <a class="citation" href="#boldt-mortensen-2024-xferbench">(Boldt &amp; Mortensen, 2024)</a>:</p> <blockquote> <p>In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the “quality” of an emergent language as its similarity to human language within a deep learning framework. We measure this by using the emergent language as pretraining data for a downstream NLP tasks in human language—the better the downstream performance, the better the emergent language. We implement this benchmark as an easy-to-use Python package that only requires a text file of utterances from the emergent language to be evaluated. Finally, we empirically test the benchmark’s validity using human, synthetic, and emergent language baselines.</p> </blockquote> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="boldt-mortensen-2024-xferbench" class="col-sm-8"> <div class="title">XferBench: a Data-Driven Benchmark for Emergent Language</div> <div class="author"> Brendon Boldt, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</em>, Jun 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the “quality” of an emergent language as its similarity to human language within a deep learning framework. We measure this by using the emergent language as pretraining data for a downstream NLP tasks in human language—the better the downstream performance, the better the emergent language. We implement this benchmark as an easy-to-use Python package that only requires a text file of utterances from the emergent language to be evaluated. Finally, we empirically test the benchmark’s validity using human, synthetic, and emergent language baselines.</p> </div> </div> </div> </li></ol> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Lexical Change | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Corpus approaches to changes in lexicons"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/6_lexical_change/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Lexical Change</h1> <p class="post-description">Corpus approaches to changes in lexicons</p> </header> <article> <p>In this project, we explore the way lexicons of languages change over time:</p> <ul> <li>Through the emergence of new words <a class="citation" href="#ryskina2020where">(Ryskina et al., 2020)</a> </li> <li>Through the decline of existing words <a class="citation" href="#francis2021quantifying">(Francis et al., 2021)</a> </li> </ul> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2021</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="francis2021quantifying" class="col-sm-8"> <div class="title">Quantifying Cognitive Factors in Lexical Decline</div> <div class="author"> David Francis, Ella Rabinovich, Farhan Samir, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David Mortensen, Suzanne Stevenson' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>Transactions of the Association for Computational Linguistics</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We adopt an evolutionary view on language change in which cognitive factors (in addition to social ones) affect the fitness of words and their success in the linguistic ecosystem. Specifically, we propose a variety of psycholinguistic factors—semantic, distributional, and phonological—that we hypothesize are predictive of lexical decline, in which words greatly decrease in frequency over time. Using historical data across three languages (English, French, and German), we find that most of our proposed factors show a significant difference in the expected direction between each curated set of declining words and their matched stable words. Moreover, logistic regression analyses show that semantic and distributional factors are significant in predicting declining words. Further diachronic analysis reveals that declining words tend to decrease in the diversity of their lexical contexts over time, gradually narrowing their ‘ecological niches’.</p> </div> </div> </div> </li></ol> <h2 class="bibliography">2020</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="ryskina2020where" class="col-sm-8"> <div class="title">Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods</div> <div class="author"> Maria Ryskina, Ella Rabinovich, Taylor Berg-Kirkpatrick, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David R. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Lexical Change | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Corpus approaches to changes in lexicons"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/6_lexical_change/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Lexical Change</h1> <p class="post-description">Corpus approaches to changes in lexicons</p> </header> <article> <p>In this project, we explore the way lexicons of languages change over time:</p> <ul> <li>Through the emergence of new words <a class="citation" href="#ryskina2020where">(Ryskina et al., 2020)</a> </li> <li>Through the decline of existing words <a class="citation" href="#francis2021quantifying">(Francis et al., 2021)</a> </li> </ul> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2021</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="francis2021quantifying" class="col-sm-8"> <div class="title">Quantifying Cognitive Factors in Lexical Decline</div> <div class="author"> David Francis, Ella Rabinovich, Farhan Samir, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David Mortensen, Suzanne Stevenson' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>Transactions of the Association for Computational Linguistics</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We adopt an evolutionary view on language change in which cognitive factors (in addition to social ones) affect the fitness of words and their success in the linguistic ecosystem. Specifically, we propose a variety of psycholinguistic factors—semantic, distributional, and phonological—that we hypothesize are predictive of lexical decline, in which words greatly decrease in frequency over time. Using historical data across three languages (English, French, and German), we find that most of our proposed factors show a significant difference in the expected direction between each curated set of declining words and their matched stable words. Moreover, logistic regression analyses show that semantic and distributional factors are significant in predicting declining words. Further diachronic analysis reveals that declining words tend to decrease in the diversity of their lexical contexts over time, gradually narrowing their ‘ecological niches’.</p> </div> </div> </div> </li></ol> <h2 class="bibliography">2020</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="ryskina2020where" class="col-sm-8"> <div class="title">Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods</div> <div class="author"> Maria Ryskina, Ella Rabinovich, Taylor Berg-Kirkpatrick, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David R. Mortensen, Yulia Tsvetkov' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Society for Computation in Linguistics</em>, Dec 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> </div> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. Powered by <a href="https://jekyllrb.com/" target="_blank" rel="external nofollow noopener">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio" rel="external nofollow noopener" target="_blank">al-folio</a> theme. Hosted by <a href="https://pages.github.com/" target="_blank" rel="external nofollow noopener">GitHub Pages</a>. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Phonological Representations for NLP | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Leveraging phonological representations for NLP tasks"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/8_phonology_for_nlp/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Phonological Representations for NLP</h1> <p class="post-description">Leveraging phonological representations for NLP tasks</p> </header> <article> <p>The ways in which phonology can be used for NLP ends is underexplored. Members of this lab paved the way for future work in this area with tools like Epitran <a class="citation" href="#mortensen2018epitran">(Mortensen et al., 2018)</a> and PanPhon <a class="citation" href="#mortensen2016panphon">(Mortensen et al., 2016)</a>. We are now seeking to apply phonological representations in a variety of tasks, following the path cleared by <a class="citation" href="#bharadwaj2016phonologically">(Bharadwaj et al., 2016)</a> and <a class="citation" href="#chaudhary2018adapting">(Chaudhary et al., 2018)</a>.</p> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2018</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018epitran" class="col-sm-8"> <div class="title">Epitran: Precision G2P for Many Languages</div> <div class="author"> David R. Mortensen, Siddharth Dalmia, and Patrick Littell </div> <div class="periodical"> <em>In Proceedings of the 11th Language Resources and Evaluation Conference</em>, May 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2018adapting" class="col-sm-8"> <div class="title">Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations</div> <div class="author"> Aditi Chaudhary, Chunting Zhou, Lori Levin, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Graham Neubig, David R. Mortensen, Jaime Carbonell' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</em>, Oct 2018 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Much work in Natural Language Processing (NLP) has been for resource-rich languages, making generalization to new, less-resourced languages challenging. We present two approaches for improving generalization to low-resourced languages by adapting continuous word representations using linguistically motivated subword units: phonemes, morphemes and graphemes. Our method requires neither parallel corpora nor bilingual dictionaries and provides a significant gain in performance over previous methods relying on these resources. We demonstrate the effectiveness of our approaches on Named Entity Recognition for four languages, namely Uyghur, Turkish, Bengali and Hindi, of which Uyghur and Bengali are low resource languages, and also perform experiments on Machine Translation. Exploiting subwords with transfer learning gives us a boost of +15.2 NER F1 for Uyghur and +9.7 F1 for Bengali. We also show improvements in the monolingual setting where we achieve (avg.) +3 F1 and (avg.) +1.35 BLEU.</p> </div> </div> </div> </li> </ol> <h2 class="bibliography">2016</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2016panphon" class="col-sm-8"> <div class="title">PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors</div> <div class="author"> David R. Mortensen, Patrick Littell, Akash Bharadwaj, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Kartik Goyal, Chris Dyer, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</em>, Dec 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper contributes to a growing body of evidence that—when coupled with appropriate machine-learning techniques–linguistically motivated, information-rich representations can outperform one-hot encodings of linguistic data. In particular, we show that phonological features outperform character-based models. PanPhon is a database relating over 5,000 IPA segments to 21 subsegmental articulatory features. We show that this database boosts performance in various NER-related tasks. Phonologically aware, neural CRF models built on PanPhon features are able to perform better on monolingual Spanish and Turkish NER tasks that character-based models. They have also been shown to work well in transfer models (as between Uzbek and Turkish). PanPhon features also contribute measurably to Orthography-to-IPA conversion tasks.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="bharadwaj2016phonologically" class="col-sm-8"> <div class="title">Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings</div> <div class="author"> Akash Bharadwaj, <em>David Mortensen</em>, Chris Dyer, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> Phonological Representations for NLP | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="Leveraging phonological representations for NLP tasks"> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/projects/8_phonology_for_nlp/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item "> <a class="nav-link" href="/publications/">publications </a> </li> <li class="nav-item active"> <a class="nav-link" href="/projects/">projects <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">Phonological Representations for NLP</h1> <p class="post-description">Leveraging phonological representations for NLP tasks</p> </header> <article> <p>The ways in which phonology can be used for NLP ends is underexplored. Members of this lab paved the way for future work in this area with tools like Epitran <a class="citation" href="#mortensen2018epitran">(Mortensen et al., 2018)</a> and PanPhon <a class="citation" href="#mortensen2016panphon">(Mortensen et al., 2016)</a>. We are now seeking to apply phonological representations in a variety of tasks, following the path cleared by <a class="citation" href="#bharadwaj2016phonologically">(Bharadwaj et al., 2016)</a> and <a class="citation" href="#chaudhary2018adapting">(Chaudhary et al., 2018)</a>.</p> </article> <h2>References</h2> <div class="publications"> <h2 class="bibliography">2018</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018epitran" class="col-sm-8"> <div class="title">Epitran: Precision G2P for Many Languages</div> <div class="author"> David R. Mortensen, Siddharth Dalmia, and Patrick Littell </div> <div class="periodical"> <em>In Proceedings of the 11th Language Resources and Evaluation Conference</em>, May 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2018adapting" class="col-sm-8"> <div class="title">Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations</div> <div class="author"> Aditi Chaudhary, Chunting Zhou, Lori Levin, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Graham Neubig, David R. Mortensen, Jaime Carbonell' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</em>, Oct 2018 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Much work in Natural Language Processing (NLP) has been for resource-rich languages, making generalization to new, less-resourced languages challenging. We present two approaches for improving generalization to low-resourced languages by adapting continuous word representations using linguistically motivated subword units: phonemes, morphemes and graphemes. Our method requires neither parallel corpora nor bilingual dictionaries and provides a significant gain in performance over previous methods relying on these resources. We demonstrate the effectiveness of our approaches on Named Entity Recognition for four languages, namely Uyghur, Turkish, Bengali and Hindi, of which Uyghur and Bengali are low resource languages, and also perform experiments on Machine Translation. Exploiting subwords with transfer learning gives us a boost of +15.2 NER F1 for Uyghur and +9.7 F1 for Bengali. We also show improvements in the monolingual setting where we achieve (avg.) +3 F1 and (avg.) +1.35 BLEU.</p> </div> </div> </div> </li> </ol> <h2 class="bibliography">2016</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2016panphon" class="col-sm-8"> <div class="title">PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors</div> <div class="author"> David R. Mortensen, Patrick Littell, Akash Bharadwaj, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Kartik Goyal, Chris Dyer, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</em>, Dec 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper contributes to a growing body of evidence that—when coupled with appropriate machine-learning techniques–linguistically motivated, information-rich representations can outperform one-hot encodings of linguistic data. In particular, we show that phonological features outperform character-based models. PanPhon is a database relating over 5,000 IPA segments to 21 subsegmental articulatory features. We show that this database boosts performance in various NER-related tasks. Phonologically aware, neural CRF models built on PanPhon features are able to perform better on monolingual Spanish and Turkish NER tasks that character-based models. They have also been shown to work well in transfer models (as between Uzbek and Turkish). PanPhon features also contribute measurably to Orthography-to-IPA conversion tasks.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="bharadwaj2016phonologically" class="col-sm-8"> <div class="title">Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings</div> <div class="author"> Akash Bharadwaj, <em>David Mortensen</em>, Chris Dyer, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 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$('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Automating Comparative Reconstruction</h2> <p class="card-text">Work on developing models that reconstruct protolanguages based on collections of cognate sets</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> <div class="col"> <a href="/projects/2_codegen/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/basel-rathaus-proj-480.webp 480w,/assets/img/basel-rathaus-proj-800.webp 800w,/assets/img/basel-rathaus-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/basel-rathaus-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Historical Linguistics as Code Generation</h2> <p class="card-text">Modeling phonological reconstruction as a code generation problem using LLMs</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> <div class="col"> <a href="/projects/6_lexical_change/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/basel-sky-proj-480.webp 480w,/assets/img/basel-sky-proj-800.webp 800w,/assets/img/basel-sky-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/basel-sky-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Lexical Change</h2> <p class="card-text">Corpus approaches to changes in lexicons</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="emergent" href=".#emergent"> <h2 class="category">emergent</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/5_xferbench/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/aareschlucht2-proj-480.webp 480w,/assets/img/aareschlucht2-proj-800.webp 800w,/assets/img/aareschlucht2-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/aareschlucht2-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">XferBench</h2> <p class="card-text">Evaluating Emergent Communication Systems with Downstream Tasks</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> <div class="col"> <a href="/projects/3_elcc/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/lake-proj-480.webp 480w,/assets/img/lake-proj-800.webp 800w,/assets/img/lake-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/lake-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Emergent Language Corpus Collection</h2> <p class="card-text">Building a collection of corpora from emergent communication systems</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="atypical" href=".#atypical"> <h2 class="category">atypical</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/7_evaluating/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/tessin-valley-480.webp 480w,/assets/img/tessin-valley-800.webp 800w,/assets/img/tessin-valley-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/tessin-valley.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Atypical Speech Assessment</h2> <p class="card-text">Assessing the degree to which speech is atypical</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="phonology" href=".#phonology"> <h2 class="category">phonology</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/8_phonology_for_nlp/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/thurgau-apple-blossoms-480.webp 480w,/assets/img/thurgau-apple-blossoms-800.webp 800w,/assets/img/thurgau-apple-blossoms-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/thurgau-apple-blossoms.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Phonological Representations for NLP</h2> <p class="card-text">Leveraging phonological representations for NLP tasks</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="llm" href=".#llm"> <h2 class="category">llm</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/4_wuggpt/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/luzern-bridge-proj-480.webp 480w,/assets/img/luzern-bridge-proj-800.webp 800w,/assets/img/luzern-bridge-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/luzern-bridge-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">WugGPT</h2> <p class="card-text">Evaluating the morphological capabilities of Large Language Models</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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$('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Automating Comparative Reconstruction</h2> <p class="card-text">Work on developing models that reconstruct protolanguages based on collections of cognate sets</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> <div class="col"> <a href="/projects/2_codegen/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/basel-rathaus-proj-480.webp 480w,/assets/img/basel-rathaus-proj-800.webp 800w,/assets/img/basel-rathaus-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/basel-rathaus-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Historical Linguistics as Code Generation</h2> <p class="card-text">Modeling phonological reconstruction as a code generation problem using LLMs</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> <div class="col"> <a href="/projects/6_lexical_change/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/basel-sky-proj-480.webp 480w,/assets/img/basel-sky-proj-800.webp 800w,/assets/img/basel-sky-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/basel-sky-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Lexical Change</h2> <p class="card-text">Corpus approaches to changes in lexicons</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="emergent" href=".#emergent"> <h2 class="category">emergent</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/5_xferbench/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/aareschlucht2-proj-480.webp 480w,/assets/img/aareschlucht2-proj-800.webp 800w,/assets/img/aareschlucht2-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/aareschlucht2-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">XferBench</h2> <p class="card-text">Evaluating Emergent Communication Systems with Downstream Tasks</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> <div class="col"> <a href="/projects/3_elcc/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/lake-proj-480.webp 480w,/assets/img/lake-proj-800.webp 800w,/assets/img/lake-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/lake-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Emergent Language Corpus Collection</h2> <p class="card-text">Building a collection of corpora from emergent communication systems</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="atypical" href=".#atypical"> <h2 class="category">atypical</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/7_evaluating/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/tessin-valley-480.webp 480w,/assets/img/tessin-valley-800.webp 800w,/assets/img/tessin-valley-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/tessin-valley.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Atypical Speech Assessment</h2> <p class="card-text">Assessing the degree to which speech is atypical</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="phonology" href=".#phonology"> <h2 class="category">phonology</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/8_phonology_for_nlp/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/thurgau-apple-blossoms-480.webp 480w,/assets/img/thurgau-apple-blossoms-800.webp 800w,/assets/img/thurgau-apple-blossoms-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/thurgau-apple-blossoms.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">Phonological Representations for NLP</h2> <p class="card-text">Leveraging phonological representations for NLP tasks</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> <a id="llm" href=".#llm"> <h2 class="category">llm</h2> </a> <div class="row row-cols-1 row-cols-md-3"> <div class="col"> <a href="/projects/4_wuggpt/"> <div class="card h-100 hoverable"> <figure> <picture> <source class="responsive-img-srcset" srcset="/assets/img/luzern-bridge-proj-480.webp 480w,/assets/img/luzern-bridge-proj-800.webp 800w,/assets/img/luzern-bridge-proj-1400.webp 1400w," sizes="250px" type="image/webp"></source> <img src="/assets/img/luzern-bridge-proj.jpg" class="card-img-top" width="100%" height="auto" alt="project thumbnail" loading="eager" onerror="this.onerror=null; $('.responsive-img-srcset').remove();"> </picture> </figure> <div class="card-body"> <h2 class="card-title">WugGPT</h2> <p class="card-text">Evaluating the morphological capabilities of Large Language Models</p> <div class="row ml-1 mr-1 p-0"> </div> </div> </div> </a> </div> </div> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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-<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> publications | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="David Mortensen's publications including all publications with other members of ChangeLing Lab."> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/publications/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item active"> <a class="nav-link" href="/publications/">publications <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">publications</h1> <p class="post-description">David Mortensen's publications including all publications with other members of ChangeLing Lab.</p> </header> <article> <script src="/assets/js/bibsearch.js?1bc438ca9037884cc579601c09afd847" type="module"></script> <p><input type="text" id="bibsearch" spellcheck="false" autocomplete="off" class="search bibsearch-form-input" placeholder="Type to filter"></p> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu2024semisupervisedneuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Semisupervised Neural Proto-Language Reconstruction</div> <div class="author"> Liang Lu, Peirong Xie, and David R. Mortensen </div> <div class="periodical"> 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="cui2024neuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Neural Proto-Language Reconstruction</div> <div class="author"> Chenxuan Cui, Ying Chen, Qinxin Wang, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="boldt2024review" class="col-sm-8"> <div class="title">A Review of the Applications of Deep Learning-Based Emergent Communication</div> <div class="author"> Brendon Boldt, and David R. Mortensen </div> <div class="periodical"> <em>Transactions on Machine Learning Research</em>, 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="zhou-etal-2024-constructions" class="col-sm-8"> <div class="title">Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons</div> <div class="author"> Shijia Zhou, Leonie Weissweiler, Taiqi He, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Hinrich Schütze, David R. Mortensen, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In this paper, we make a contribution that can be understood from two perspectives: from an NLP perspective, we introduce a small challenge dataset for NLI with large lexical overlap, which minimises the possibility of models discerning entailment solely based on token distinctions, and show that GPT-4 and Llama 2 fail it with strong bias. We then create further challenging sub-tasks in an effort to explain this failure. From a Computational Linguistics perspective, we identify a group of constructions with three classes of adjectives which cannot be distinguished by surface features. This enables us to probe for LLM’s understanding of these constructions in various ways, and we find that they fail in a variety of ways to distinguish between them, suggesting that they don’t adequately represent their meaning or capture the lexical properties of phrasal heads.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu-etal-2024-improved" class="col-sm-8"> <div class="title">Improved Neural Protoform Reconstruction via Reflex Prediction</div> <div class="author"> Liang Lu, Jingzhi Wang, and David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protolanguage reconstruction is central to historical linguistics. The comparative method, one of the most influential theoretical and methodological frameworks in the history of the language sciences, allows linguists to infer protoforms (reconstructed ancestral words) from their reflexes (related modern words) based on the assumption of regular sound change. Not surprisingly, numerous computational linguists have attempted to operationalize comparative reconstruction through various computational models, the most successful of which have been supervised encoder-decoder models, which treat the problem of predicting protoforms given sets of reflexes as a sequence-to-sequence problem. We argue that this framework ignores one of the most important aspects of the comparative method: not only should protoforms be inferable from cognate sets (sets of related reflexes) but the reflexes should also be inferable from the protoforms. Leveraging another line of research—reflex prediction—we propose a system in which candidate protoforms from a reconstruction model are reranked by a reflex prediction model. We show that this more complete implementation of the comparative method allows us to surpass state-of-the-art protoform reconstruction methods on three of four Chinese and Romance datasets.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="shim-etal-2024-phonotactic" class="col-sm-8"> <div class="title">Phonotactic Complexity across Dialects</div> <div class="author"> Ryan Soh-Eun Shim, Kalvin Chang, and David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Received wisdom in linguistic typology holds that if the structure of a language becomes more complex in one dimension, it will simplify in another, building on the assumption that all languages are equally complex (Joseph and Newmeyer, 2012). We study this claim on a micro-level, using a tightly-controlled sample of Dutch dialects (across 366 collection sites) and Min dialects (across 60 sites), which enables a more fair comparison across varieties. Even at the dialect level, we find empirical evidence for a tradeoff between word length and a computational measure of phonotactic complexity from a LSTM-based phone-level language model—a result previously documented only at the language level. A generalized additive model (GAM) shows that dialects with low phonotactic complexity concentrate around the capital regions, which we hypothesize to correspond to prior hypotheses that language varieties of greater or more diverse populations show reduced phonotactic complexity. We also experiment with incorporating the auxiliary task of predicting syllable constituency, but do not find an increase in the strength of the negative correlation observed.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="zouhar-etal-2024-pwesuite" class="col-sm-8"> <div class="title">PWESuite: Phonetic Word Embeddings and Tasks They Facilitate</div> <div class="author"> Vilém Zouhar, Kalvin Chang, Chenxuan Cui, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Nate B. Carlson, Nathaniel Romney Robinson, Mrinmaya Sachan, David R. Mortensen' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Mapping words into a fixed-dimensional vector space is the backbone of modern NLP. While most word embedding methods successfully encode semantic information, they overlook phonetic information that is crucial for many tasks. We develop three methods that use articulatory features to build phonetically informed word embeddings. To address the inconsistent evaluation of existing phonetic word embedding methods, we also contribute a task suite to fairly evaluate past, current, and future methods. We evaluate both (1) intrinsic aspects of phonetic word embeddings, such as word retrieval and correlation with sound similarity, and (2) extrinsic performance on tasks such as rhyme and cognate detection and sound analogies. We hope our task suite will promote reproducibility and inspire future phonetic embedding research.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen-etal-2024-verbing" class="col-sm-8"> <div class="title">Verbing Weirds Language (Models): Evaluation of English Zero-Derivation in Five LLMs</div> <div class="author"> David R. Mortensen, Valentina Izrailevitch, Yunze Xiao, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Hinrich Schütze, Leonie Weissweiler' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Lexical-syntactic flexibility, in the form of conversion (or zero-derivation) is a hallmark of English morphology. In conversion, a word with one part of speech is placed in a non-prototypical context, where it is coerced to behave as if it had a different part of speech. However, while this process affects a large part of the English lexicon, little work has been done to establish the degree to which language models capture this type of generalization. This paper reports the first study on the behavior of large language models with reference to conversion. We design a task for testing lexical-syntactic flexibility—the degree to which models can generalize over words in a construction with a non-prototypical part of speech. This task is situated within a natural language inference paradigm. We test the abilities of five language models—two proprietary models (GPT-3.5 and GPT-4), three open source model (Mistral 7B, Falcon 40B, and Llama 2 70B). We find that GPT-4 performs best on the task, followed by GPT-3.5, but that the open source language models are also able to perform it and that the 7-billion parameter Mistral displays as little difference between its baseline performance on the natural language inference task and the non-prototypical syntactic category task, as the massive GPT-4.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="boldt-mortensen-2024-xferbench" class="col-sm-8"> <div class="title">XferBench: a Data-Driven Benchmark for Emergent Language</div> <div class="author"> Brendon Boldt, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</em>, Jun 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the “quality” of an emergent language as its similarity to human language within a deep learning framework. We measure this by using the emergent language as pretraining data for a downstream NLP tasks in human language—the better the downstream performance, the better the emergent language. We implement this benchmark as an easy-to-use Python package that only requires a text file of utterances from the emergent language to be evaluated. Finally, we empirically test the benchmark’s validity using human, synthetic, and emergent language baselines.</p> </div> </div> </div> </li> </ol> <h2 class="bibliography">2023</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2023kuki" class="col-sm-8"> <div class="title">Kuki-Chin Phonology: An Overview</div> <div class="author"> David R Mortensen </div> <div class="periodical"> <em>Himalayan Linguistics</em>, Jun 2023 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2023african" class="col-sm-8"> <div class="title">African Substrates Rather Than European Lexifiers to Augment African-diaspora Creole Translation</div> <div class="author"> Nathaniel Romney Robinson, Matthew Dean Stutzman, Stephen D. Richardson, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In 4th Workshop on African Natural Language Processing</em>, Jun 2023 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chang2023automating" class="col-sm-8"> <div class="title">Automating Sound Change Prediction for Phylogenetic Inference: A Tukanoan Case Study</div> <div class="author"> Kalvin Chang, Nathaniel Robinson, Anna Cai, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Ting Chen, Annie Zhang, David Mortensen' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We describe a set of new methods to partially automate linguistic phylogenetic inference given (1) cognate sets with their respective protoforms and sound laws, (2) a mapping from phones to their articulatory features and (3) a typological database of sound changes.We train a neural network on these sound change data to weight articulatory distances between phones and predict intermediate sound change steps between historical protoforms and their modern descendants, replacing a linguistic expert in part of a parsimony-based phylogenetic inference algorithm. In our best experiments on Tukanoan languages, this method produces trees with a Generalized Quartet Distance of 0.12 from a tree that used expert annotations, a significant improvement over other semi-automated baselines. We discuss potential benefits and drawbacks to our neural approach and parsimony-based tree prediction. We also experiment with a minimal generalization learner for automatic sound law induction, finding it less effective than sound laws from expert annotation. Our code is publicly available.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2023chatgpt" class="col-sm-8"> <div class="title">ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages</div> <div class="author"> Nathaniel Robinson, Perez Ogayo, David R. Mortensen, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Graham Neubig' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the Eighth Conference on Machine Translation</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Large language models (LLMs) implicitly learn to perform a range of language tasks, including machine translation (MT). Previous studies explore aspects of LLMs’ MT capabilities. However, there exist a wide variety of languages for which recent LLM MT performance has never before been evaluated. Without published experimental evidence on the matter, it is difficult for speakers of the world’s diverse languages to know how and whether they can use LLMs for their languages. We present the first experimental evidence for an expansive set of 204 languages, along with MT cost analysis, using the FLORES-200 benchmark. Trends reveal that GPT models approach or exceed traditional MT model performance for some high-resource languages (HRLs) but consistently lag for low-resource languages (LRLs), under-performing traditional MT for 84.1% of languages we covered. Our analysis reveals that a language’s resource level is the most important feature in determining ChatGPT’s relative ability to translate it, and suggests that ChatGPT is especially disadvantaged for LRLs and African languages.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="ahia2023languages" class="col-sm-8"> <div class="title">Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models</div> <div class="author"> Orevaoghene Ahia, Sachin Kumar, Hila Gonen, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Jungo Kasai, David Mortensen, Noah Smith, Yulia Tsvetkov' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of these products. The API vendors charge their users based on usage, more specifically on the number of “tokens” processed or generated by the underlying language models. What constitutes a token, however, is training data and model dependent with a large variance in the number of tokens required to convey the same information in different languages. In this work, we analyze the effect of this non-uniformity on the fairness of an API’s pricing policy across languages. We conduct a systematic analysis of the cost and utility of OpenAI’s language model API on multilingual benchmarks in 22 typologically diverse languages. We show evidence that speakers of a large number of the supported languages are overcharged while obtaining poorer results. These speakers tend to also come from regions where the APIs are less affordable, to begin with. Through these analyses, we aim to increase transparency around language model APIs’ pricing policies and encourage the vendors to make them more equitable.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="weissweiler2023counting" class="col-sm-8"> <div class="title">Counting the Bugs in ChatGPT’s Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model</div> <div class="author"> Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, and <span class="more-authors" title="click to view 10 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '10 more authors' ? 'Anna Cai, Ritam Dutt, Amey Hengle, Anubha Kabra, Atharva Kulkarni, Abhishek Vijayakumar, Haofei Yu, Hinrich Schuetze, Kemal Oflazer, David Mortensen' : '10 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">10 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relatively few systematic inquiries into the linguistic capabilities of the latest generation of LLMs, and those studies that do exist (i) ignore the remarkable ability of humans to generalize, (ii) focus only on English, and (iii) investigate syntax or semantics and overlook other capabilities that lie at the heart of human language, like morphology. Here, we close these gaps by conducting the first rigorous analysis of the morphological capabilities of ChatGPT in four typologically varied languages (specifically, English, German, Tamil, and Turkish). We apply a version of Berko’s (1958) wug test to ChatGPT, using novel, uncontaminated datasets for the four examined languages. We find that ChatGPT massively underperforms purpose-built systems, particularly in English. Overall, our results—through the lens of morphology—cast a new light on the linguistic capabilities of ChatGPT, suggesting that claims of human-like language skills are premature and misleading.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="feng2023calibrated" class="col-sm-8"> <div class="title">Calibrated Seq2seq Models for Efficient and Generalizable Ultra-fine Entity Typing</div> <div class="author"> Yanlin Feng, Adithya Pratapa, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Findings of the Association for Computational Linguistics: EMNLP 2023</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Ultra-fine entity typing plays a crucial role in information extraction by predicting fine-grained semantic types for entity mentions in text. However, this task poses significant challenges due to the massive number of entity types in the output space. The current state-of-the-art approaches, based on standard multi-label classifiers or cross-encoder models, suffer from poor generalization performance or inefficient inference speed. In this paper, we present CASENT, a seq2seq model designed for ultra-fine entity typing that predicts ultra-fine types with calibrated confidence scores. Our model takes an entity mention as input and employs constrained beam search to generate multiple types autoregressively. The raw sequence probabilities associated with the predicted types are then transformed into confidence scores using a novel calibration method. We conduct extensive experiments on the UFET dataset which contains over 10k types. Our method outperforms the previous state-of-the-art in terms of F1 score and calibration error, while achieving an inference speedup of over 50 times. Additionally, we demonstrate the generalization capabilities of our model by evaluating it in zero-shot and few-shot settings on five specialized domain entity typing datasets that are unseen during training. Remarkably, our model outperforms large language models with 10 times more parameters in the zero-shot setting, and when fine-tuned on 50 examples, it significantly outperforms ChatGPT on all datasets.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="weissweiler2023construction" class="col-sm-8"> <div class="title">Construction Grammar Provides Unique Insight into Neural Language Models</div> <div class="author"> Leonie Weissweiler, Taiqi He, Naoki Otani, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'David R. Mortensen, Lori Levin, Hinrich Schütze' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)</em>, Mar 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Construction Grammar (CxG) has recently been used as the basis for probing studies that have investigated the performance of large pretrained language models (PLMs) with respect to the structure and meaning of constructions. In this position paper, we make suggestions for the continuation and augmentation of this line of research. We look at probing methodology that was not designed with CxG in mind, as well as probing methodology that was designed for specific constructions. We analyse selected previous work in detail, and provide our view of the most important challenges and research questions that this promising new field faces.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="kim2023transformed" class="col-sm-8"> <div class="title">Transformed Protoform Reconstruction</div> <div class="author"> Young Min Kim, Kalvin Chang, Chenxuan Cui, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protoform reconstruction is the task of inferring what morphemes or words appeared like in the ancestral languages of a set of daughter languages. Meloni et al (2021) achieved the state-of-the-art on Latin protoform reconstruction with an RNN-based encoder-decoder with attention model. We update their model with the state-of-the-art seq2seq model: the Transformer. Our model outperforms their model on a suite of different metrics on two different datasets: their Romance data of 8,000 cognates spanning 5 languages and a Chinese dataset (Hou 2004) of 800+ cognates spanning 39 varieties. We also probe our model for potential phylogenetic signal contained in the model. Our code is publicly available at \urlhttps://github.com/cmu-llab/acl-2023.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2023generalized" class="col-sm-8"> <div class="title">Generalized Glossing Guidelines: An Explicit, Human- and Machine-Readable, Item-and-Process Convention for Morphological Annotation</div> <div class="author"> David R. Mortensen, Ela Gulsen, Taiqi He, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Nathaniel Robinson, Jonathan Amith, Lindia Tjuatja, Lori Levin' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Interlinear glossing provides a vital type of morphosyntactic annotation, both for linguists and language revitalists, and numerous conventions exist for representing it formally and computationally. Some of these formats are human readable; others are machine readable. Some are easy to edit with general-purpose tools. Few represent non-concatentative processes like infixation, reduplication, mutation, truncation, and tonal overwriting in a consistent and formally rigorous way (on par with affixation). We propose an annotation conventionâ€”Generalized Glossing Guidelines (GGG) that combines all of these positive properties using an Item-and-Process (IP) framework. We describe the format, demonstrate its linguistic adequacy, and compare it with two other interlinear glossed text annotation schemes.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="karakasidis2023multilingual" class="col-sm-8"> <div class="title">Multilingual TTS Accent Impressions for Accented ASR</div> <div class="author"> Georgios Karakasidis, Nathaniel Robinson, Yaroslav Getman, and <span class="more-authors" title="click to view 6 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '6 more authors' ? 'Atieno Ogayo, Ragheb Al-Ghezi, Ananya Ayasi, Shinji Watanabe, David R Mortensen, Mikko Kurimo' : '6 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">6 more authors</span> </div> <div class="periodical"> <em>In International Conference on Text, Speech, and Dialogue</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="he2023sigmorefun" class="col-sm-8"> <div class="title">SigMoreFun Submission to the SIGMORPHON Shared Task on Interlinear Glossing</div> <div class="author"> Taiqi He, Lindia Tjuatja, Nathaniel Robinson, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Shinji Watanabe, David R. Mortensen, Graham Neubig, Lori Levin' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In our submission to the SIGMORPHON 2023 Shared Task on interlinear glossing (IGT), we explore approaches to data augmentation and modeling across seven low-resource languages. For data augmentation, we explore two approaches: creating artificial data from the provided training data and utilizing existing IGT resources in other languages. On the modeling side, we test an enhanced version of the provided token classification baseline as well as a pretrained multilingual seq2seq model. Additionally, we apply post-correction using a dictionary for Gitksan, the language with the smallest amount of data. We find that our token classification models are the best performing, with the highest word-level accuracy for Arapaho and highest morpheme-level accuracy for Gitksan out of all submissions. We also show that data augmentation is an effective strategy, though applying artificial data pretraining has very different effects across both models tested.</p> </div> </div> </div> </li> </ol> <h2 class="bibliography">2022</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2022data" class="col-sm-8"> <div class="title">Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican</div> <div class="author"> Nathaniel Robinson, Cameron Hogan, Nancy Fulda, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Multilingual transfer techniques often improve low-resource machine translation (MT). Many of these techniques are applied without considering data characteristics. We show in the context of Haitian-to-English translation that transfer effectiveness is correlated with amount of training data and relationships between knowledge-sharing languages. Our experiments suggest that for some languages beyond a threshold of authentic data, back-translation augmentation methods are counterproductive, while cross-lingual transfer from a sufficiently related language is preferred. We complement this finding by contributing a rule-based French-Haitian orthographic and syntactic engine and a novel method for phonological embedding. When used with multilingual techniques, orthographic transformation makes statistically significant improvements over conventional methods. And in very low-resource Jamaican MT, code-switching with a transfer language for orthographic resemblance yields a 6.63 BLEU point advantage.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chang2022wikihan" class="col-sm-8"> <div class="title">WikiHan: A New Comparative Dataset for Chinese Languages</div> <div class="author"> Kalvin Chang, Chenxuan Cui, Youngmin Kim, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In COLING 2022</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2022tts" class="col-sm-8"> <div class="title">When Is TTS Augmentation Through a Pivot Language Useful?</div> <div class="author"> Nathaniel Romney Robinson, Perez Ogayo, Swetha R. Gangu, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David R. Mortensen, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Interspeech 2022</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022speech" class="col-sm-8"> <div class="title">Speech Recognition for Around 2000 Languages without Audio</div> <div class="author"> Xinjian Li, Florian Metze, David R. Mortensen, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Alan W. Black, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Interspeech 2022</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2022hmong" class="col-sm-8"> <div class="title">A Hmong Corpus with Elaborate Expression Annotations</div> <div class="author"> David R. Mortensen, Xinyu Zhang, Chenxuan Cui, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Katherine J. Zhang' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022phone" class="col-sm-8"> <div class="title">Phone Inventories and Recognition for Every Language</div> <div class="author"> Xinjian Li, Florian Metze, David R. Mortensen, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Alan W. Black, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="marr2022large" class="col-sm-8"> <div class="title">Large-Scale Computerized Forward Reconstruction Yields New Perspectives in French Diachronic Phonology</div> <div class="author"> Clayton Marr, and <em>David Mortensen</em> </div> <div class="periodical"> <em>Diachronica</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022zero" class="col-sm-8"> <div class="title">Zero-shot Learning for Grapheme to Phoneme Conversion with Language Ensemble</div> <div class="author"> Xinjian Li, Florian Metze, <em>David Mortensen</em>, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Shinji Watanabe, Alan Black' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Findings of the Association for Computational Linguistics: ACL 2022</em>, May 2022 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Grapheme-to-Phoneme (G2P) has many applications in NLP and speech fields. Most existing work focuses heavily on languages with abundant training datasets, which limits the scope of target languages to less than 100 languages. This work attempts to apply zero-shot learning to approximate G2P models for all low-resource and endangered languages in Glottolog (about 8k languages). For any unseen target language, we first build the phylogenetic tree (i.e. language family tree) to identify top-k nearest languages for which we have training sets. Then we run models of those languages to obtain a hypothesis set, which we combine into a confusion network to propose a most likely hypothesis as an approximation to the target language. We test our approach on over 600 unseen languages and demonstrate it significantly outperforms baselines.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="cui2022learning" class="col-sm-8"> <div class="title">Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese</div> <div class="author"> Chenxuan Cui, Katherine Zhang, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies</em>, Jul 2022 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Coordinate compounds (CCs) and elaborate expressions (EEs) are coordinate constructions common in languages of East and Southeast Asia. Mortensen (2006) claims that (1) the linear ordering of EEs and CCs in Hmong, Lahu, and Chinese can be predicted via phonological hierarchies and (2) that these phonological hierarchies lack a clear phonetic rationale. These claims are signficant because morphosyntax has often been seen as in a feed-forward relationship with phonology, and phonological generalizations have often been assumed to be phonetically “natural”. We investigate whether the ordering of CCs and EEs can be learned empirically and whether computational models (classifiers and sequence-labeling models) learn unnatural hierarchies similar to those posited by Mortensen (2006). We find that decision trees and SVMs learn to predict the order of CCs/EEs on the basis of phonology, beating strong baselines for all three languages, with DTs learning hierarchies strikingly similar to those proposed by Mortensen. However, we also find that a neural sequence labeling model is able to learn the ordering of elaborate expressions in Hmong very effectively without using any phonological information. We argue that EE ordering can be learned through two independent routes: phonology and lexical distribution, presenting a more nuanced picture than previous work.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2022wfst4strsw" class="col-sm-8"> <div class="title">Wfst4Str</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jul 2022 </div> <div class="periodical"> Rust/Python library for working with strings using weighted finite state transducers </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2021</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022asr2k" class="col-sm-8"> <div class="title">ASR2K: Speech Recognition for Around 2000 Languages without Audio</div> <div class="author"> </div> <div class="periodical"> <em>In Interspeech 2022</em>, Jul 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="francis2021quantifying" class="col-sm-8"> <div class="title">Quantifying Cognitive Factors in Lexical Decline</div> <div class="author"> David Francis, Ella Rabinovich, Farhan Samir, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David Mortensen, Suzanne Stevenson' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>Transactions of the Association for Computational Linguistics</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We adopt an evolutionary view on language change in which cognitive factors (in addition to social ones) affect the fitness of words and their success in the linguistic ecosystem. Specifically, we propose a variety of psycholinguistic factors—semantic, distributional, and phonological—that we hypothesize are predictive of lexical decline, in which words greatly decrease in frequency over time. Using historical data across three languages (English, French, and German), we find that most of our proposed factors show a significant difference in the expected direction between each curated set of declining words and their matched stable words. Moreover, logistic regression analyses show that semantic and distributional factors are significant in predicting declining words. Further diachronic analysis reveals that declining words tend to decrease in the diversity of their lexical contexts over time, gradually narrowing their ‘ecological niches’.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2021multilingual" class="col-sm-8"> <div class="title">Multilingual phonetic dataset for low resource speech recognition</div> <div class="author"> Xinjian Li, David R Mortensen, Florian Metze, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Alan W. Black' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In ICASSP 2021</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2021east" class="col-sm-8"> <div class="title">East Tusom: A phonetic and phonological sketch of a largely undocumented Tangkhulic language</div> <div class="author"> David R. Mortensen, and Jordan Picone </div> <div class="periodical"> Dec 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>East Tusom is a Tibeto-Burman language of Manipur, India, belonging to the Tangkhulic group. While it shares some innovations with the other Tangkhulic languages, it differs markedly from “Standard Tangkhul” (which is based on the speech of Ukhrul town). Past documentation is limited to a small set of hastily transcribed forms in a comparative reconstruction of Tangkhulic rhymes (Mortensen &amp; Miller 2013; Mortensen 2012). This paper presents the first substantial sketch of an aspect of the language: its (descriptive) phonetics and phonology. The data are based on recordings of an extensive wordlist (730 items) and one short text, all from one fluent native speaker in her mid-twenties. We present the phonetic inventory of East Tusom and a phonemicization, with exhaustive examples. We also present an overview of the major phonological patterns and generalizations in the language. Of special interest are a “placeless nasal” that is realized as nasalization on the preceding vowel unless it is followed by a consonant, and numerous plosive-fricative clusters (where the fricative is roughly homorganic with the following vowel) that have developed from historical aspirated plosives. A complete wordlist, organized by gloss and semantic field, is provided as appendices.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2021tusom2021" class="col-sm-8"> <div class="title">Tusom2021: A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments</div> <div class="author"> David R. Mortensen, Jordan Picone, Xinjian Li, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Kathleen Siminyu' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proc. Interspeech 2021</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="pratapa2021evaluating" class="col-sm-8"> <div class="title">Evaluating the Morphosyntactic Well-formedness of Generated Texts</div> <div class="author"> Adithya Pratapa, Antonios Anastasopoulos, Shruti Rijhwani, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Aditi Chaudhary, David R. Mortensen, Graham Neubig, Yulia Tsvetkov' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Text generation systems are ubiquitous in natural language processing applications. However, evaluation of these systems remains a challenge, especially in multilingual settings. In this paper, we propose L’AMBRE – a metric to evaluate the morphosyntactic well-formedness of text using its dependency parse and morphosyntactic rules of the language. We present a way to automatically extract various rules governing morphosyntax directly from dependency treebanks. To tackle the noisy outputs from text generation systems, we propose a simple methodology to train robust parsers. We show the effectiveness of our metric on the task of machine translation through a diachronic study of systems translating into morphologically-rich languages.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="siminyu2021phoneme" class="col-sm-8"> <div class="title">Phoneme Recognition Through Fine Tuning of Phonetic Representations: A Case Study on Luhya Language Varieties</div> <div class="author"> Kathleen Siminyu, Xinjian Li, Antonios Anastasopoulos, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'David R. Mortensen, Michael R. Marlo, Graham Neubig' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proc. Interspeech 2021</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="sun2021ranking" class="col-sm-8"> <div class="title">Ranking Transfer Languages with Pragmatically-Motivated Features for Multilingual Sentiment Analysis</div> <div class="author"> Jimin Sun, Hwijeen Ahn, Chan Young Park, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Yulia Tsvetkov, David R. Mortensen' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In EACL 2021</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="yan2021differentiable" class="col-sm-8"> <div class="title">Differentiable Allophone Graphs for Language-Universal Speech Recognition</div> <div class="author"> Brian Yan, Siddharth Dalmia, David R. Mortensen, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Florian Metze, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proc. Interspeech 2021</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2020</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2020automatic" class="col-sm-8"> <div class="title">Automatic Extraction of Rules Governing Morphological Agreement</div> <div class="author"> Aditi Chaudhary, Antonios Anastasopoulos, Adithya Pratapa, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'David R. Mortensen, Zaid Sheikh, Yulia Tsvetkov, Graham Neubig' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2020toward" class="col-sm-8"> <div class="title">Towards Zero-shot Learning for Automatic Phonemic Transcription</div> <div class="author"> Xinjian Li, Siddharth Dalmia, David R. Mortensen, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Juncheng Li, Alan Black, Florian Metze' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2020universal" class="col-sm-8"> <div class="title">Universal Phone Recognition with a Multilingual Allophone System</div> <div class="author"> Xinjian Li, Siddharth Dalmia, Juncheng Li, and <span class="more-authors" title="click to view 8 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '8 more authors' ? 'Matthew Lee, Patrick Littell, Jiali Yao, Antonios Anastasopoulos, David R. Mortensen, Graham Neubig, Alan W Black, Florian Metze' : '8 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">8 more authors</span> </div> <div class="periodical"> <em>In ICASSP 2020</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="marr2020computerized" class="col-sm-8"> <div class="title">Computerized Forward Reconstruction for Analysis in Diachronic Phonology, and Latin to French Reflex Prediction</div> <div class="author"> Clayton Marr, and David R. Mortensen </div> <div class="periodical"> <em>In 1st Workshop on Language Technologies for Historical and Ancient LAnguages (LT4HALA)</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="memon2020characterizing" class="col-sm-8"> <div class="title">Characterizing Sociolinguistic Variation in the Competing Vaccination Communities</div> <div class="author"> Shahan Ali Memon, Aman Tyagi, David R. Mortensen, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Kathleen M Carley' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the International Conference SBP-BRiMS 2020</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2020allovera" class="col-sm-8"> <div class="title">AlloVera: A Multilingual Allophone Database</div> <div class="author"> David R. Mortensen, Xinjian Li, Patrick Littell, and <span class="more-authors" title="click to view 6 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '6 more authors' ? 'Alexis Michaud, Shruti Rijhwani, Antonios Anastasopoulos, Alan W. Black, Florian Metze, Graham Neubig' : '6 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">6 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC 2020)</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="ryskina2020where" class="col-sm-8"> <div class="title">Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods</div> <div class="author"> Maria Ryskina, Ella Rabinovich, Taylor Berg-Kirkpatrick, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David R. Mortensen, Yulia Tsvetkov' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Society for Computation in Linguistics</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2019</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2019cmu" class="col-sm-8"> <div class="title">CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology</div> <div class="author"> Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'David R. Mortensen, Jaime Carbonell, Yulia Tsvetkov' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology</em>, Aug 2019 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS, Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2019hmong" class="col-sm-8"> <div class="title">Hmong (Mong Leng)</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In The Mainland Southeast Asia Linguistic Area</em>, Aug 2019 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2019indomorphsw" class="col-sm-8"> <div class="title">IndoMorph</div> <div class="author"> David R. Mortensen, and Jong Hyuk Park </div> <div class="periodical"> Aug 2019 </div> <div class="periodical"> Collection of Foma FST morphological analyzers for languages of the Indian subcontinent </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2018</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2018adapting" class="col-sm-8"> <div class="title">Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations</div> <div class="author"> Aditi Chaudhary, Chunting Zhou, Lori Levin, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Graham Neubig, David R. Mortensen, Jaime Carbonell' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</em>, Oct 2018 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Much work in Natural Language Processing (NLP) has been for resource-rich languages, making generalization to new, less-resourced languages challenging. We present two approaches for improving generalization to low-resourced languages by adapting continuous word representations using linguistically motivated subword units: phonemes, morphemes and graphemes. Our method requires neither parallel corpora nor bilingual dictionaries and provides a significant gain in performance over previous methods relying on these resources. We demonstrate the effectiveness of our approaches on Named Entity Recognition for four languages, namely Uyghur, Turkish, Bengali and Hindi, of which Uyghur and Bengali are low resource languages, and also perform experiments on Machine Translation. Exploiting subwords with transfer learning gives us a boost of +15.2 NER F1 for Uyghur and +9.7 F1 for Bengali. We also show improvements in the monolingual setting where we achieve (avg.) +3 F1 and (avg.) +1.35 BLEU.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2018ariel" class="col-sm-8"> <div class="title">The ARIEL-CMU situation frame detection pipeline for LoReHLT16: a model translation approach</div> <div class="author"> Patrick Littell, Tian Tian, Ruochen Xu, and <span class="more-authors" title="click to view 12 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '12 more authors' ? 'Zaid Sheikh, David Mortensen, Lori Levin, Francis Tyers, Hiroaki Hayashi, Graham Horwood, Steve Sloto, Emily Tagtow, Alan Black, Yiming Yang, Teruko Mitamura, Eduard Hovy' : '12 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">12 more authors</span> </div> <div class="periodical"> <em>Machine Translation</em>, Oct 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2018parser" class="col-sm-8"> <div class="title">Parser combinators for Tigrinya and Oromo morphology</div> <div class="author"> Patrick Littell, Tom McCoy, Na-Rae Han, and <span class="more-authors" title="click to view 5 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '5 more authors' ? 'Shruti Rijhwani, Zaid Sheikh, David Mortensen, Teruko Mitamura, Lori Levin' : '5 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">5 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 11th Language Resources and Evaluation Conference</em>, May 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018epitran" class="col-sm-8"> <div class="title">Epitran: Precision G2P for Many Languages</div> <div class="author"> David R. Mortensen, Siddharth Dalmia, and Patrick Littell </div> <div class="periodical"> <em>In Proceedings of the 11th Language Resources and Evaluation Conference</em>, May 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018epitransw" class="col-sm-8"> <div class="title">Epitran</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> May 2018 </div> <div class="periodical"> Precision orthography-to-IPA conversion for 65 languages </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018mstemsw" class="col-sm-8"> <div class="title">MStem</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> May 2018 </div> <div class="periodical"> Python multilingual morphological stemming framework and stemmer collection </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2017</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2017uriel" class="col-sm-8"> <div class="title">URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors</div> <div class="author"> Patrick Littell, David R. Mortensen, Ke Lin, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Katherine Kairis, Carlisle Turner, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers</em>, Apr 2017 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We introduce the URIEL knowledge base for massively multilingual NLP and thelang2vec utility, which provides information-rich vector identifications oflanguages drawn from typological, geographical, and phylogenetic databases andnormalized to have straightforward and consistent formats, naming, andsemantics. The goal of URIEL and lang2vec is to enable multilingual NLP,especially on less-resourced languages and make possible types of experiments(especially but not exclusively related to NLP tasks) that are otherwisedifficult or impossible due to the sparsity and incommensurability of the datasources. lang2vec vectors have been shown to reduce perplexity in multilinguallanguage modeling, when compared to one-hot language identification vectors.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2017hmong" class="col-sm-8"> <div class="title">Hmong-Mien Languages</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Oxford Research Encyclopedia of Linguistics</em>, May 2017 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2017hmongmienbib" class="col-sm-8"> <div class="title">Hmong-Mien Languages</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Oxford Bibliographies in Linguistics</em>, May 2017 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2016</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="bharadwaj2016phonologically" class="col-sm-8"> <div class="title">Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings</div> <div class="author"> Akash Bharadwaj, <em>David Mortensen</em>, Chris Dyer, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Jaime Carbonell' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing</em>, Nov 2016 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2016bridge" class="col-sm-8"> <div class="title">Bridge-Language Capitalization Inference in Western Iranian: Sorani, Kurmanji, Zazaki, and Tajik</div> <div class="author"> Patrick Littell, David R. Mortensen, Kartik Goyal, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Chris Dyer, Lori Levin' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)</em>, May 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In Sorani Kurdish, one of the most useful orthographic features in named-entity recognition – capitalization – is absent, as the language’s Perso-Arabic script does not make a distinction between uppercase and lowercase letters. We describe a system for deriving an inferred capitalization value from closely related languages by phonological similarity, and illustrate the system using several related Western Iranian languages.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2016named" class="col-sm-8"> <div class="title">Named Entity Recognition for Linguistic Rapid Response in Low-Resource Languages: Sorani Kurdish and Tajik</div> <div class="author"> Patrick Littell, Kartik Goyal, David R. Mortensen, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Alexa Little, Chris Dyer, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</em>, Dec 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper describes our construction of named-entity recognition (NER) systems in two Western Iranian languages, Sorani Kurdish and Tajik, as a part of a pilot study of “Linguistic Rapid Response” to potential emergency humanitarian relief situations. In the absence of large annotated corpora, parallel corpora, treebanks, bilingual lexica, etc., we found the following to be effective: exploiting distributional regularities in monolingual data, projecting information across closely related languages, and utilizing human linguist judgments. We show promising results on both a four-month exercise in Sorani and a two-day exercise in Tajik, achieved with minimal annotation costs.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2016panphon" class="col-sm-8"> <div class="title">PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors</div> <div class="author"> David R. Mortensen, Patrick Littell, Akash Bharadwaj, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Kartik Goyal, Chris Dyer, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</em>, Dec 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper contributes to a growing body of evidence that—when coupled with appropriate machine-learning techniques–linguistically motivated, information-rich representations can outperform one-hot encodings of linguistic data. In particular, we show that phonological features outperform character-based models. PanPhon is a database relating over 5,000 IPA segments to 21 subsegmental articulatory features. We show that this database boosts performance in various NER-related tasks. Phonologically aware, neural CRF models built on PanPhon features are able to perform better on monolingual Spanish and Turkish NER tasks that character-based models. They have also been shown to work well in transfer models (as between Uzbek and Turkish). PanPhon features also contribute measurably to Orthography-to-IPA conversion tasks.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2016panphonsw" class="col-sm-8"> <div class="title">PanPhon</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Dec 2016 </div> <div class="periodical"> Articulatory feature extractor and library </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="tsvetkov2016polyglot" class="col-sm-8"> <div class="title">Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning</div> <div class="author"> Yulia Tsvetkov, Sunayana Sitaram, Manaal Faruqui, and <span class="more-authors" title="click to view 6 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '6 more authors' ? 'Guillaume Lample, Patrick Littell, David Mortensen, Alan W Black, Lori Levin, Chris Dyer' : '6 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">6 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies</em>, Jun 2016 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2013</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2013lexical" class="col-sm-8"> <div class="title">Lexical Prefixes and Tibeto-Burman Laryngeal Contrasts</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the Thirty-Seventh Annual Meeting of the Berkeley Linguistics Society (BLS 37)</em>, Jun 2013 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2013reconstruction" class="col-sm-8"> <div class="title">A Reconstruction of Proto-Tangkhulic Rhymes</div> <div class="author"> David R. Mortensen, and James A. Miller </div> <div class="periodical"> <em>Linguistics of the Tibeto-Burman Area </em>, Jun 2013 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2013tonally" class="col-sm-8"> <div class="title">Tonally Conditioned Vowel Raising in Shuijingping Mang</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Journal of East Asian Linguistics</em>, Jun 2013 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2012</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2011sorbung" class="col-sm-8"> <div class="title">Sorbung, an Undescribed Language of Manipur: Its Phonology and Place in Tibeto-Burman</div> <div class="author"> David R. Mortensen, and Jennifer Keogh </div> <div class="periodical"> <em>Journal of the Southeast Asian Linguistics Society</em>, Jun 2012 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2012emergence" class="col-sm-8"> <div class="title">The Emergence of Obstruents after High Vowels</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Diachronica</em>, Jun 2012 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2012netspesw" class="col-sm-8"> <div class="title">NetSPE</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jun 2012 </div> <div class="periodical"> A web-based application for exploring rule-based analyses of phonological data </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="vercellotti2012classification" class="col-sm-8"> <div class="title">A Classification of Compounding in American Sign Language: an Evaluation of the Bisetto and Scalise Framework</div> <div class="author"> Mary Lou Vercellotti, and David R. Mortensen </div> <div class="periodical"> <em>Morphology</em>, Jun 2012 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2011</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2011hsspesw" class="col-sm-8"> <div class="title">HsSPE</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jun 2011 </div> <div class="periodical"> Haskell library implementing SPE-style rule-based phonology </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2011webcomparatorsw" class="col-sm-8"> <div class="title">Web Comparator</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jun 2011 </div> <div class="periodical"> A web-based application for organizing and analyzing comparative lexical databases. Used in the production of “Emergence of Obstruents” and “Proto-Tangkhulic Rhymes” </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2004</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2004emergence" class="col-sm-8"> <div class="title">The emergence of dorsal stops after high vowels in Huishu</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the Thirtieth Annual Meeting of the Berkeley Linguistics Society (BLS 30)</em>, Jun 2004 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> <h2 class="bibliography">2003</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2003baheng" class="col-sm-8"> <div class="title">Review of \emphBaheng Yu Yanjiu [research on the Pa-Hng language] by Mao Zongwu and Li Yunbing</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Linguistics of the Tibeto-Burman Area</em>, Jun 2003 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> <h2 class="bibliography">2002</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen20002langue" class="col-sm-8"> <div class="title">Review of \emphLes langue Hmong-Mjen: phonologie historique by Barbara Niederer</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Linguistics of the Tibeto-Burman Area</em>, Jun 2002 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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+<!DOCTYPE html> <html lang="en"> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <title> publications | ChangeLing Lab </title> <meta name="author" content="ChangeLing Lab"> <meta name="description" content="David Mortensen's publications including all publications with other members of ChangeLing Lab."> <meta name="keywords" content="linguistics, computational-linguistics, natural-language-processing, diachronic, phonology, morphology, sociolinguistics"> <link rel="stylesheet" href="/assets/css/bootstrap.min.css?a4b3f509e79c54a512b890d73235ef04"> <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/mdbootstrap@4.20.0/css/mdb.min.css" integrity="sha256-jpjYvU3G3N6nrrBwXJoVEYI/0zw8htfFnhT9ljN3JJw=" crossorigin="anonymous"> <link defer rel="stylesheet" href="/assets/css/academicons.min.css?f0b7046b84e425c55f3463ac249818f5"> <link defer rel="stylesheet" type="text/css" href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Roboto+Slab:100,300,400,500,700|Material+Icons&amp;display=swap"> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-github.css?591dab5a4e56573bf4ef7fd332894c99" media="" id="highlight_theme_light"> <link rel="shortcut icon" href="data:image/svg+xml,&lt;svg%20xmlns=%22http://www.w3.org/2000/svg%22%20viewBox=%220%200%20100%20100%22&gt;&lt;text%20y=%22.9em%22%20font-size=%2290%22&gt;%CA%A7&lt;/text&gt;&lt;/svg&gt;"> <link rel="stylesheet" href="/assets/css/main.css?d41d8cd98f00b204e9800998ecf8427e"> <link rel="canonical" href="https://changelinglab.github.io/publications/"> <script src="/assets/js/theme.js?9a0c749ec5240d9cda97bc72359a72c0"></script> <link defer rel="stylesheet" href="/assets/css/jekyll-pygments-themes-native.css?5847e5ed4a4568527aa6cfab446049ca" media="none" id="highlight_theme_dark"> <script>initTheme();</script> </head> <body class="fixed-top-nav "> <header> <nav id="navbar" class="navbar navbar-light navbar-expand-sm fixed-top" role="navigation"> <div class="container"> <a class="navbar-brand title font-weight-lighter" href="/"> <span class="font-weight-bold">ChangeLing</span> Lab </a> <button class="navbar-toggler collapsed ml-auto" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar top-bar"></span> <span class="icon-bar middle-bar"></span> <span class="icon-bar bottom-bar"></span> </button> <div class="collapse navbar-collapse text-right" id="navbarNav"> <ul class="navbar-nav ml-auto flex-nowrap"> <li class="nav-item "> <a class="nav-link" href="/">about </a> </li> <li class="nav-item "> <a class="nav-link" href="/blog/">blog </a> </li> <li class="nav-item active"> <a class="nav-link" href="/publications/">publications <span class="sr-only">(current)</span> </a> </li> <li class="nav-item "> <a class="nav-link" href="/projects/">projects </a> </li> <li class="nav-item "> <a class="nav-link" href="/people/">people </a> </li> <li class="nav-item"> <button id="search-toggle" title="Search" onclick="openSearchModal()"> <span class="nav-link">ctrl k <i class="ti ti-search"></i></span> </button> </li> <li class="toggle-container"> <button id="light-toggle" title="Change theme"> <i class="ti ti-sun-moon" id="light-toggle-system"></i> <i class="ti ti-moon-filled" id="light-toggle-dark"></i> <i class="ti ti-sun-filled" id="light-toggle-light"></i> </button> </li> </ul> </div> </div> </nav> <progress id="progress" value="0"> <div class="progress-container"> <span class="progress-bar"></span> </div> </progress> </header> <div class="container mt-5" role="main"> <div class="post"> <header class="post-header"> <h1 class="post-title">publications</h1> <p class="post-description">David Mortensen's publications including all publications with other members of ChangeLing Lab.</p> </header> <article> <script src="/assets/js/bibsearch.js?1bc438ca9037884cc579601c09afd847" type="module"></script> <p><input type="text" id="bibsearch" spellcheck="false" autocomplete="off" class="search bibsearch-form-input" placeholder="Type to filter"></p> <div class="publications"> <h2 class="bibliography">2024</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu2024semisupervisedneuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Semisupervised Neural Proto-Language Reconstruction</div> <div class="author"> Liang Lu, Peirong Xie, and David R. Mortensen </div> <div class="periodical"> 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="cui2024neuralprotolanguagereconstruction" class="col-sm-8"> <div class="title">Neural Proto-Language Reconstruction</div> <div class="author"> Chenxuan Cui, Ying Chen, Qinxin Wang, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="boldt2024review" class="col-sm-8"> <div class="title">A Review of the Applications of Deep Learning-Based Emergent Communication</div> <div class="author"> Brendon Boldt, and David R. Mortensen </div> <div class="periodical"> <em>Transactions on Machine Learning Research</em>, 2024 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="zhou-etal-2024-constructions" class="col-sm-8"> <div class="title">Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons</div> <div class="author"> Shijia Zhou, Leonie Weissweiler, Taiqi He, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Hinrich Schütze, David R. Mortensen, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In this paper, we make a contribution that can be understood from two perspectives: from an NLP perspective, we introduce a small challenge dataset for NLI with large lexical overlap, which minimises the possibility of models discerning entailment solely based on token distinctions, and show that GPT-4 and Llama 2 fail it with strong bias. We then create further challenging sub-tasks in an effort to explain this failure. From a Computational Linguistics perspective, we identify a group of constructions with three classes of adjectives which cannot be distinguished by surface features. This enables us to probe for LLM’s understanding of these constructions in various ways, and we find that they fail in a variety of ways to distinguish between them, suggesting that they don’t adequately represent their meaning or capture the lexical properties of phrasal heads.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="lu-etal-2024-improved" class="col-sm-8"> <div class="title">Improved Neural Protoform Reconstruction via Reflex Prediction</div> <div class="author"> Liang Lu, Jingzhi Wang, and David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protolanguage reconstruction is central to historical linguistics. The comparative method, one of the most influential theoretical and methodological frameworks in the history of the language sciences, allows linguists to infer protoforms (reconstructed ancestral words) from their reflexes (related modern words) based on the assumption of regular sound change. Not surprisingly, numerous computational linguists have attempted to operationalize comparative reconstruction through various computational models, the most successful of which have been supervised encoder-decoder models, which treat the problem of predicting protoforms given sets of reflexes as a sequence-to-sequence problem. We argue that this framework ignores one of the most important aspects of the comparative method: not only should protoforms be inferable from cognate sets (sets of related reflexes) but the reflexes should also be inferable from the protoforms. Leveraging another line of research—reflex prediction—we propose a system in which candidate protoforms from a reconstruction model are reranked by a reflex prediction model. We show that this more complete implementation of the comparative method allows us to surpass state-of-the-art protoform reconstruction methods on three of four Chinese and Romance datasets.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="shim-etal-2024-phonotactic" class="col-sm-8"> <div class="title">Phonotactic Complexity across Dialects</div> <div class="author"> Ryan Soh-Eun Shim, Kalvin Chang, and David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Received wisdom in linguistic typology holds that if the structure of a language becomes more complex in one dimension, it will simplify in another, building on the assumption that all languages are equally complex (Joseph and Newmeyer, 2012). We study this claim on a micro-level, using a tightly-controlled sample of Dutch dialects (across 366 collection sites) and Min dialects (across 60 sites), which enables a more fair comparison across varieties. Even at the dialect level, we find empirical evidence for a tradeoff between word length and a computational measure of phonotactic complexity from a LSTM-based phone-level language model—a result previously documented only at the language level. A generalized additive model (GAM) shows that dialects with low phonotactic complexity concentrate around the capital regions, which we hypothesize to correspond to prior hypotheses that language varieties of greater or more diverse populations show reduced phonotactic complexity. We also experiment with incorporating the auxiliary task of predicting syllable constituency, but do not find an increase in the strength of the negative correlation observed.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="zouhar-etal-2024-pwesuite" class="col-sm-8"> <div class="title">PWESuite: Phonetic Word Embeddings and Tasks They Facilitate</div> <div class="author"> Vilém Zouhar, Kalvin Chang, Chenxuan Cui, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Nate B. Carlson, Nathaniel Romney Robinson, Mrinmaya Sachan, David R. Mortensen' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Mapping words into a fixed-dimensional vector space is the backbone of modern NLP. While most word embedding methods successfully encode semantic information, they overlook phonetic information that is crucial for many tasks. We develop three methods that use articulatory features to build phonetically informed word embeddings. To address the inconsistent evaluation of existing phonetic word embedding methods, we also contribute a task suite to fairly evaluate past, current, and future methods. We evaluate both (1) intrinsic aspects of phonetic word embeddings, such as word retrieval and correlation with sound similarity, and (2) extrinsic performance on tasks such as rhyme and cognate detection and sound analogies. We hope our task suite will promote reproducibility and inspire future phonetic embedding research.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen-etal-2024-verbing" class="col-sm-8"> <div class="title">Verbing Weirds Language (Models): Evaluation of English Zero-Derivation in Five LLMs</div> <div class="author"> David R. Mortensen, Valentina Izrailevitch, Yunze Xiao, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Hinrich Schütze, Leonie Weissweiler' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</em>, May 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Lexical-syntactic flexibility, in the form of conversion (or zero-derivation) is a hallmark of English morphology. In conversion, a word with one part of speech is placed in a non-prototypical context, where it is coerced to behave as if it had a different part of speech. However, while this process affects a large part of the English lexicon, little work has been done to establish the degree to which language models capture this type of generalization. This paper reports the first study on the behavior of large language models with reference to conversion. We design a task for testing lexical-syntactic flexibility—the degree to which models can generalize over words in a construction with a non-prototypical part of speech. This task is situated within a natural language inference paradigm. We test the abilities of five language models—two proprietary models (GPT-3.5 and GPT-4), three open source model (Mistral 7B, Falcon 40B, and Llama 2 70B). We find that GPT-4 performs best on the task, followed by GPT-3.5, but that the open source language models are also able to perform it and that the 7-billion parameter Mistral displays as little difference between its baseline performance on the natural language inference task and the non-prototypical syntactic category task, as the massive GPT-4.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="boldt-mortensen-2024-xferbench" class="col-sm-8"> <div class="title">XferBench: a Data-Driven Benchmark for Emergent Language</div> <div class="author"> Brendon Boldt, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</em>, Jun 2024 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the “quality” of an emergent language as its similarity to human language within a deep learning framework. We measure this by using the emergent language as pretraining data for a downstream NLP tasks in human language—the better the downstream performance, the better the emergent language. We implement this benchmark as an easy-to-use Python package that only requires a text file of utterances from the emergent language to be evaluated. Finally, we empirically test the benchmark’s validity using human, synthetic, and emergent language baselines.</p> </div> </div> </div> </li> </ol> <h2 class="bibliography">2023</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2023kuki" class="col-sm-8"> <div class="title">Kuki-Chin Phonology: An Overview</div> <div class="author"> David R Mortensen </div> <div class="periodical"> <em>Himalayan Linguistics</em>, Jun 2023 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2023african" class="col-sm-8"> <div class="title">African Substrates Rather Than European Lexifiers to Augment African-diaspora Creole Translation</div> <div class="author"> Nathaniel Romney Robinson, Matthew Dean Stutzman, Stephen D. Richardson, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In 4th Workshop on African Natural Language Processing</em>, Jun 2023 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chang2023automating" class="col-sm-8"> <div class="title">Automating Sound Change Prediction for Phylogenetic Inference: A Tukanoan Case Study</div> <div class="author"> Kalvin Chang, Nathaniel Robinson, Anna Cai, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Ting Chen, Annie Zhang, David Mortensen' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We describe a set of new methods to partially automate linguistic phylogenetic inference given (1) cognate sets with their respective protoforms and sound laws, (2) a mapping from phones to their articulatory features and (3) a typological database of sound changes.We train a neural network on these sound change data to weight articulatory distances between phones and predict intermediate sound change steps between historical protoforms and their modern descendants, replacing a linguistic expert in part of a parsimony-based phylogenetic inference algorithm. In our best experiments on Tukanoan languages, this method produces trees with a Generalized Quartet Distance of 0.12 from a tree that used expert annotations, a significant improvement over other semi-automated baselines. We discuss potential benefits and drawbacks to our neural approach and parsimony-based tree prediction. We also experiment with a minimal generalization learner for automatic sound law induction, finding it less effective than sound laws from expert annotation. Our code is publicly available.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2023chatgpt" class="col-sm-8"> <div class="title">ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages</div> <div class="author"> Nathaniel Robinson, Perez Ogayo, David R. Mortensen, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Graham Neubig' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the Eighth Conference on Machine Translation</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Large language models (LLMs) implicitly learn to perform a range of language tasks, including machine translation (MT). Previous studies explore aspects of LLMs’ MT capabilities. However, there exist a wide variety of languages for which recent LLM MT performance has never before been evaluated. Without published experimental evidence on the matter, it is difficult for speakers of the world’s diverse languages to know how and whether they can use LLMs for their languages. We present the first experimental evidence for an expansive set of 204 languages, along with MT cost analysis, using the FLORES-200 benchmark. Trends reveal that GPT models approach or exceed traditional MT model performance for some high-resource languages (HRLs) but consistently lag for low-resource languages (LRLs), under-performing traditional MT for 84.1% of languages we covered. Our analysis reveals that a language’s resource level is the most important feature in determining ChatGPT’s relative ability to translate it, and suggests that ChatGPT is especially disadvantaged for LRLs and African languages.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="ahia2023languages" class="col-sm-8"> <div class="title">Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models</div> <div class="author"> Orevaoghene Ahia, Sachin Kumar, Hila Gonen, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Jungo Kasai, David Mortensen, Noah Smith, Yulia Tsvetkov' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Language models have graduated from being research prototypes to commercialized products offered as web APIs, and recent works have highlighted the multilingual capabilities of these products. The API vendors charge their users based on usage, more specifically on the number of “tokens” processed or generated by the underlying language models. What constitutes a token, however, is training data and model dependent with a large variance in the number of tokens required to convey the same information in different languages. In this work, we analyze the effect of this non-uniformity on the fairness of an API’s pricing policy across languages. We conduct a systematic analysis of the cost and utility of OpenAI’s language model API on multilingual benchmarks in 22 typologically diverse languages. We show evidence that speakers of a large number of the supported languages are overcharged while obtaining poorer results. These speakers tend to also come from regions where the APIs are less affordable, to begin with. Through these analyses, we aim to increase transparency around language model APIs’ pricing policies and encourage the vendors to make them more equitable.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="weissweiler2023counting" class="col-sm-8"> <div class="title">Counting the Bugs in ChatGPT’s Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model</div> <div class="author"> Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, and <span class="more-authors" title="click to view 10 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '10 more authors' ? 'Anna Cai, Ritam Dutt, Amey Hengle, Anubha Kabra, Atharva Kulkarni, Abhishek Vijayakumar, Haofei Yu, Hinrich Schuetze, Kemal Oflazer, David Mortensen' : '10 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">10 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relatively few systematic inquiries into the linguistic capabilities of the latest generation of LLMs, and those studies that do exist (i) ignore the remarkable ability of humans to generalize, (ii) focus only on English, and (iii) investigate syntax or semantics and overlook other capabilities that lie at the heart of human language, like morphology. Here, we close these gaps by conducting the first rigorous analysis of the morphological capabilities of ChatGPT in four typologically varied languages (specifically, English, German, Tamil, and Turkish). We apply a version of Berko’s (1958) wug test to ChatGPT, using novel, uncontaminated datasets for the four examined languages. We find that ChatGPT massively underperforms purpose-built systems, particularly in English. Overall, our results—through the lens of morphology—cast a new light on the linguistic capabilities of ChatGPT, suggesting that claims of human-like language skills are premature and misleading.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="feng2023calibrated" class="col-sm-8"> <div class="title">Calibrated Seq2seq Models for Efficient and Generalizable Ultra-fine Entity Typing</div> <div class="author"> Yanlin Feng, Adithya Pratapa, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Findings of the Association for Computational Linguistics: EMNLP 2023</em>, Dec 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Ultra-fine entity typing plays a crucial role in information extraction by predicting fine-grained semantic types for entity mentions in text. However, this task poses significant challenges due to the massive number of entity types in the output space. The current state-of-the-art approaches, based on standard multi-label classifiers or cross-encoder models, suffer from poor generalization performance or inefficient inference speed. In this paper, we present CASENT, a seq2seq model designed for ultra-fine entity typing that predicts ultra-fine types with calibrated confidence scores. Our model takes an entity mention as input and employs constrained beam search to generate multiple types autoregressively. The raw sequence probabilities associated with the predicted types are then transformed into confidence scores using a novel calibration method. We conduct extensive experiments on the UFET dataset which contains over 10k types. Our method outperforms the previous state-of-the-art in terms of F1 score and calibration error, while achieving an inference speedup of over 50 times. Additionally, we demonstrate the generalization capabilities of our model by evaluating it in zero-shot and few-shot settings on five specialized domain entity typing datasets that are unseen during training. Remarkably, our model outperforms large language models with 10 times more parameters in the zero-shot setting, and when fine-tuned on 50 examples, it significantly outperforms ChatGPT on all datasets.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="weissweiler2023construction" class="col-sm-8"> <div class="title">Construction Grammar Provides Unique Insight into Neural Language Models</div> <div class="author"> Leonie Weissweiler, Taiqi He, Naoki Otani, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'David R. Mortensen, Lori Levin, Hinrich Schütze' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the First International Workshop on Construction Grammars and NLP (CxGs+NLP, GURT/SyntaxFest 2023)</em>, Mar 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Construction Grammar (CxG) has recently been used as the basis for probing studies that have investigated the performance of large pretrained language models (PLMs) with respect to the structure and meaning of constructions. In this position paper, we make suggestions for the continuation and augmentation of this line of research. We look at probing methodology that was not designed with CxG in mind, as well as probing methodology that was designed for specific constructions. We analyse selected previous work in detail, and provide our view of the most important challenges and research questions that this promising new field faces.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="kim2023transformed" class="col-sm-8"> <div class="title">Transformed Protoform Reconstruction</div> <div class="author"> Young Min Kim, Kalvin Chang, Chenxuan Cui, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Protoform reconstruction is the task of inferring what morphemes or words appeared like in the ancestral languages of a set of daughter languages. Meloni et al (2021) achieved the state-of-the-art on Latin protoform reconstruction with an RNN-based encoder-decoder with attention model. We update their model with the state-of-the-art seq2seq model: the Transformer. Our model outperforms their model on a suite of different metrics on two different datasets: their Romance data of 8,000 cognates spanning 5 languages and a Chinese dataset (Hou 2004) of 800+ cognates spanning 39 varieties. We also probe our model for potential phylogenetic signal contained in the model. Our code is publicly available at \urlhttps://github.com/cmu-llab/acl-2023.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2023generalized" class="col-sm-8"> <div class="title">Generalized Glossing Guidelines: An Explicit, Human- and Machine-Readable, Item-and-Process Convention for Morphological Annotation</div> <div class="author"> David R. Mortensen, Ela Gulsen, Taiqi He, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Nathaniel Robinson, Jonathan Amith, Lindia Tjuatja, Lori Levin' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Interlinear glossing provides a vital type of morphosyntactic annotation, both for linguists and language revitalists, and numerous conventions exist for representing it formally and computationally. Some of these formats are human readable; others are machine readable. Some are easy to edit with general-purpose tools. Few represent non-concatentative processes like infixation, reduplication, mutation, truncation, and tonal overwriting in a consistent and formally rigorous way (on par with affixation). We propose an annotation conventionâ€”Generalized Glossing Guidelines (GGG) that combines all of these positive properties using an Item-and-Process (IP) framework. We describe the format, demonstrate its linguistic adequacy, and compare it with two other interlinear glossed text annotation schemes.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="karakasidis2023multilingual" class="col-sm-8"> <div class="title">Multilingual TTS Accent Impressions for Accented ASR</div> <div class="author"> Georgios Karakasidis, Nathaniel Robinson, Yaroslav Getman, and <span class="more-authors" title="click to view 6 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '6 more authors' ? 'Atieno Ogayo, Ragheb Al-Ghezi, Ananya Ayasi, Shinji Watanabe, David R Mortensen, Mikko Kurimo' : '6 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">6 more authors</span> </div> <div class="periodical"> <em>In International Conference on Text, Speech, and Dialogue</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="he2023sigmorefun" class="col-sm-8"> <div class="title">SigMoreFun Submission to the SIGMORPHON Shared Task on Interlinear Glossing</div> <div class="author"> Taiqi He, Lindia Tjuatja, Nathaniel Robinson, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Shinji Watanabe, David R. Mortensen, Graham Neubig, Lori Levin' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology</em>, Jul 2023 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In our submission to the SIGMORPHON 2023 Shared Task on interlinear glossing (IGT), we explore approaches to data augmentation and modeling across seven low-resource languages. For data augmentation, we explore two approaches: creating artificial data from the provided training data and utilizing existing IGT resources in other languages. On the modeling side, we test an enhanced version of the provided token classification baseline as well as a pretrained multilingual seq2seq model. Additionally, we apply post-correction using a dictionary for Gitksan, the language with the smallest amount of data. We find that our token classification models are the best performing, with the highest word-level accuracy for Arapaho and highest morpheme-level accuracy for Gitksan out of all submissions. We also show that data augmentation is an effective strategy, though applying artificial data pretraining has very different effects across both models tested.</p> </div> </div> </div> </li> </ol> <h2 class="bibliography">2022</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2022data" class="col-sm-8"> <div class="title">Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican</div> <div class="author"> Nathaniel Robinson, Cameron Hogan, Nancy Fulda, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Multilingual transfer techniques often improve low-resource machine translation (MT). Many of these techniques are applied without considering data characteristics. We show in the context of Haitian-to-English translation that transfer effectiveness is correlated with amount of training data and relationships between knowledge-sharing languages. Our experiments suggest that for some languages beyond a threshold of authentic data, back-translation augmentation methods are counterproductive, while cross-lingual transfer from a sufficiently related language is preferred. We complement this finding by contributing a rule-based French-Haitian orthographic and syntactic engine and a novel method for phonological embedding. When used with multilingual techniques, orthographic transformation makes statistically significant improvements over conventional methods. And in very low-resource Jamaican MT, code-switching with a transfer language for orthographic resemblance yields a 6.63 BLEU point advantage.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chang2022wikihan" class="col-sm-8"> <div class="title">WikiHan: A New Comparative Dataset for Chinese Languages</div> <div class="author"> Kalvin Chang, Chenxuan Cui, Youngmin Kim, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'David R. Mortensen' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In COLING 2022</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="robinson2022tts" class="col-sm-8"> <div class="title">When Is TTS Augmentation Through a Pivot Language Useful?</div> <div class="author"> Nathaniel Romney Robinson, Perez Ogayo, Swetha R. Gangu, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David R. Mortensen, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Interspeech 2022</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022speech" class="col-sm-8"> <div class="title">Speech Recognition for Around 2000 Languages without Audio</div> <div class="author"> Xinjian Li, Florian Metze, David R. Mortensen, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Alan W. Black, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Interspeech 2022</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2022hmong" class="col-sm-8"> <div class="title">A Hmong Corpus with Elaborate Expression Annotations</div> <div class="author"> David R. Mortensen, Xinyu Zhang, Chenxuan Cui, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Katherine J. Zhang' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022phone" class="col-sm-8"> <div class="title">Phone Inventories and Recognition for Every Language</div> <div class="author"> Xinjian Li, Florian Metze, David R. Mortensen, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Alan W. Black, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="marr2022large" class="col-sm-8"> <div class="title">Large-Scale Computerized Forward Reconstruction Yields New Perspectives in French Diachronic Phonology</div> <div class="author"> Clayton Marr, and <em>David Mortensen</em> </div> <div class="periodical"> <em>Diachronica</em>, Oct 2022 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022zero" class="col-sm-8"> <div class="title">Zero-shot Learning for Grapheme to Phoneme Conversion with Language Ensemble</div> <div class="author"> Xinjian Li, Florian Metze, <em>David Mortensen</em>, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Shinji Watanabe, Alan Black' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Findings of the Association for Computational Linguistics: ACL 2022</em>, May 2022 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Grapheme-to-Phoneme (G2P) has many applications in NLP and speech fields. Most existing work focuses heavily on languages with abundant training datasets, which limits the scope of target languages to less than 100 languages. This work attempts to apply zero-shot learning to approximate G2P models for all low-resource and endangered languages in Glottolog (about 8k languages). For any unseen target language, we first build the phylogenetic tree (i.e. language family tree) to identify top-k nearest languages for which we have training sets. Then we run models of those languages to obtain a hypothesis set, which we combine into a confusion network to propose a most likely hypothesis as an approximation to the target language. We test our approach on over 600 unseen languages and demonstrate it significantly outperforms baselines.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="cui2022learning" class="col-sm-8"> <div class="title">Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese</div> <div class="author"> Chenxuan Cui, Katherine Zhang, and <em>David Mortensen</em> </div> <div class="periodical"> <em>In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies</em>, Jul 2022 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Coordinate compounds (CCs) and elaborate expressions (EEs) are coordinate constructions common in languages of East and Southeast Asia. Mortensen (2006) claims that (1) the linear ordering of EEs and CCs in Hmong, Lahu, and Chinese can be predicted via phonological hierarchies and (2) that these phonological hierarchies lack a clear phonetic rationale. These claims are signficant because morphosyntax has often been seen as in a feed-forward relationship with phonology, and phonological generalizations have often been assumed to be phonetically “natural”. We investigate whether the ordering of CCs and EEs can be learned empirically and whether computational models (classifiers and sequence-labeling models) learn unnatural hierarchies similar to those posited by Mortensen (2006). We find that decision trees and SVMs learn to predict the order of CCs/EEs on the basis of phonology, beating strong baselines for all three languages, with DTs learning hierarchies strikingly similar to those proposed by Mortensen. However, we also find that a neural sequence labeling model is able to learn the ordering of elaborate expressions in Hmong very effectively without using any phonological information. We argue that EE ordering can be learned through two independent routes: phonology and lexical distribution, presenting a more nuanced picture than previous work.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2022wfst4strsw" class="col-sm-8"> <div class="title">Wfst4Str</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jul 2022 </div> <div class="periodical"> Rust/Python library for working with strings using weighted finite state transducers </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2021</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2022asr2k" class="col-sm-8"> <div class="title">ASR2K: Speech Recognition for Around 2000 Languages without Audio</div> <div class="author"> </div> <div class="periodical"> <em>In Interspeech 2022</em>, Jul 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="francis2021quantifying" class="col-sm-8"> <div class="title">Quantifying Cognitive Factors in Lexical Decline</div> <div class="author"> David Francis, Ella Rabinovich, Farhan Samir, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David Mortensen, Suzanne Stevenson' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>Transactions of the Association for Computational Linguistics</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We adopt an evolutionary view on language change in which cognitive factors (in addition to social ones) affect the fitness of words and their success in the linguistic ecosystem. Specifically, we propose a variety of psycholinguistic factors—semantic, distributional, and phonological—that we hypothesize are predictive of lexical decline, in which words greatly decrease in frequency over time. Using historical data across three languages (English, French, and German), we find that most of our proposed factors show a significant difference in the expected direction between each curated set of declining words and their matched stable words. Moreover, logistic regression analyses show that semantic and distributional factors are significant in predicting declining words. Further diachronic analysis reveals that declining words tend to decrease in the diversity of their lexical contexts over time, gradually narrowing their ‘ecological niches’.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2021multilingual" class="col-sm-8"> <div class="title">Multilingual phonetic dataset for low resource speech recognition</div> <div class="author"> Xinjian Li, David R Mortensen, Florian Metze, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Alan W. Black' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In ICASSP 2021</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2021east" class="col-sm-8"> <div class="title">East Tusom: A phonetic and phonological sketch of a largely undocumented Tangkhulic language</div> <div class="author"> David R. Mortensen, and Jordan Picone </div> <div class="periodical"> Dec 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>East Tusom is a Tibeto-Burman language of Manipur, India, belonging to the Tangkhulic group. While it shares some innovations with the other Tangkhulic languages, it differs markedly from “Standard Tangkhul” (which is based on the speech of Ukhrul town). Past documentation is limited to a small set of hastily transcribed forms in a comparative reconstruction of Tangkhulic rhymes (Mortensen &amp; Miller 2013; Mortensen 2012). This paper presents the first substantial sketch of an aspect of the language: its (descriptive) phonetics and phonology. The data are based on recordings of an extensive wordlist (730 items) and one short text, all from one fluent native speaker in her mid-twenties. We present the phonetic inventory of East Tusom and a phonemicization, with exhaustive examples. We also present an overview of the major phonological patterns and generalizations in the language. Of special interest are a “placeless nasal” that is realized as nasalization on the preceding vowel unless it is followed by a consonant, and numerous plosive-fricative clusters (where the fricative is roughly homorganic with the following vowel) that have developed from historical aspirated plosives. A complete wordlist, organized by gloss and semantic field, is provided as appendices.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2021tusom2021" class="col-sm-8"> <div class="title">Tusom2021: A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments</div> <div class="author"> David R. Mortensen, Jordan Picone, Xinjian Li, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Kathleen Siminyu' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proc. Interspeech 2021</em>, Dec 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="pratapa2021evaluating" class="col-sm-8"> <div class="title">Evaluating the Morphosyntactic Well-formedness of Generated Texts</div> <div class="author"> Adithya Pratapa, Antonios Anastasopoulos, Shruti Rijhwani, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'Aditi Chaudhary, David R. Mortensen, Graham Neubig, Yulia Tsvetkov' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Text generation systems are ubiquitous in natural language processing applications. However, evaluation of these systems remains a challenge, especially in multilingual settings. In this paper, we propose L’AMBRE – a metric to evaluate the morphosyntactic well-formedness of text using its dependency parse and morphosyntactic rules of the language. We present a way to automatically extract various rules governing morphosyntax directly from dependency treebanks. To tackle the noisy outputs from text generation systems, we propose a simple methodology to train robust parsers. We show the effectiveness of our metric on the task of machine translation through a diachronic study of systems translating into morphologically-rich languages.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="siminyu2021phoneme" class="col-sm-8"> <div class="title">Phoneme Recognition Through Fine Tuning of Phonetic Representations: A Case Study on Luhya Language Varieties</div> <div class="author"> Kathleen Siminyu, Xinjian Li, Antonios Anastasopoulos, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'David R. Mortensen, Michael R. Marlo, Graham Neubig' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proc. Interspeech 2021</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="sun2021ranking" class="col-sm-8"> <div class="title">Ranking Transfer Languages with Pragmatically-Motivated Features for Multilingual Sentiment Analysis</div> <div class="author"> Jimin Sun, Hwijeen Ahn, Chan Young Park, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Yulia Tsvetkov, David R. Mortensen' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In EACL 2021</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="yan2021differentiable" class="col-sm-8"> <div class="title">Differentiable Allophone Graphs for Language-Universal Speech Recognition</div> <div class="author"> Brian Yan, Siddharth Dalmia, David R. Mortensen, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Florian Metze, Shinji Watanabe' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proc. Interspeech 2021</em>, Nov 2021 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2020</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2020automatic" class="col-sm-8"> <div class="title">Automatic Extraction of Rules Governing Morphological Agreement</div> <div class="author"> Aditi Chaudhary, Antonios Anastasopoulos, Adithya Pratapa, and <span class="more-authors" title="click to view 4 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '4 more authors' ? 'David R. Mortensen, Zaid Sheikh, Yulia Tsvetkov, Graham Neubig' : '4 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">4 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2020toward" class="col-sm-8"> <div class="title">Towards Zero-shot Learning for Automatic Phonemic Transcription</div> <div class="author"> Xinjian Li, Siddharth Dalmia, David R. Mortensen, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Juncheng Li, Alan Black, Florian Metze' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="li2020universal" class="col-sm-8"> <div class="title">Universal Phone Recognition with a Multilingual Allophone System</div> <div class="author"> Xinjian Li, Siddharth Dalmia, Juncheng Li, and <span class="more-authors" title="click to view 8 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '8 more authors' ? 'Matthew Lee, Patrick Littell, Jiali Yao, Antonios Anastasopoulos, David R. Mortensen, Graham Neubig, Alan W Black, Florian Metze' : '8 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">8 more authors</span> </div> <div class="periodical"> <em>In ICASSP 2020</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="marr2020computerized" class="col-sm-8"> <div class="title">Computerized Forward Reconstruction for Analysis in Diachronic Phonology, and Latin to French Reflex Prediction</div> <div class="author"> Clayton Marr, and David R. Mortensen </div> <div class="periodical"> <em>In 1st Workshop on Language Technologies for Historical and Ancient LAnguages (LT4HALA)</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="memon2020characterizing" class="col-sm-8"> <div class="title">Characterizing Sociolinguistic Variation in the Competing Vaccination Communities</div> <div class="author"> Shahan Ali Memon, Aman Tyagi, David R. Mortensen, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Kathleen M Carley' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the International Conference SBP-BRiMS 2020</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2020allovera" class="col-sm-8"> <div class="title">AlloVera: A Multilingual Allophone Database</div> <div class="author"> David R. Mortensen, Xinjian Li, Patrick Littell, and <span class="more-authors" title="click to view 6 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '6 more authors' ? 'Alexis Michaud, Shruti Rijhwani, Antonios Anastasopoulos, Alan W. Black, Florian Metze, Graham Neubig' : '6 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">6 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC 2020)</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="ryskina2020where" class="col-sm-8"> <div class="title">Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods</div> <div class="author"> Maria Ryskina, Ella Rabinovich, Taylor Berg-Kirkpatrick, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'David R. Mortensen, Yulia Tsvetkov' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Society for Computation in Linguistics</em>, Nov 2020 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2019</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2019cmu" class="col-sm-8"> <div class="title">CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology</div> <div class="author"> Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'David R. Mortensen, Jaime Carbonell, Yulia Tsvetkov' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology</em>, Aug 2019 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS, Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2019hmong" class="col-sm-8"> <div class="title">Hmong (Mong Leng)</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In The Mainland Southeast Asia Linguistic Area</em>, Aug 2019 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2019indomorphsw" class="col-sm-8"> <div class="title">IndoMorph</div> <div class="author"> David R. Mortensen, and Jong Hyuk Park </div> <div class="periodical"> Aug 2019 </div> <div class="periodical"> Collection of Foma FST morphological analyzers for languages of the Indian subcontinent </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2018</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="chaudhary2018adapting" class="col-sm-8"> <div class="title">Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations</div> <div class="author"> Aditi Chaudhary, Chunting Zhou, Lori Levin, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Graham Neubig, David R. Mortensen, Jaime Carbonell' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</em>, Oct 2018 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>Much work in Natural Language Processing (NLP) has been for resource-rich languages, making generalization to new, less-resourced languages challenging. We present two approaches for improving generalization to low-resourced languages by adapting continuous word representations using linguistically motivated subword units: phonemes, morphemes and graphemes. Our method requires neither parallel corpora nor bilingual dictionaries and provides a significant gain in performance over previous methods relying on these resources. We demonstrate the effectiveness of our approaches on Named Entity Recognition for four languages, namely Uyghur, Turkish, Bengali and Hindi, of which Uyghur and Bengali are low resource languages, and also perform experiments on Machine Translation. Exploiting subwords with transfer learning gives us a boost of +15.2 NER F1 for Uyghur and +9.7 F1 for Bengali. We also show improvements in the monolingual setting where we achieve (avg.) +3 F1 and (avg.) +1.35 BLEU.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2018ariel" class="col-sm-8"> <div class="title">The ARIEL-CMU situation frame detection pipeline for LoReHLT16: a model translation approach</div> <div class="author"> Patrick Littell, Tian Tian, Ruochen Xu, and <span class="more-authors" title="click to view 12 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '12 more authors' ? 'Zaid Sheikh, David Mortensen, Lori Levin, Francis Tyers, Hiroaki Hayashi, Graham Horwood, Steve Sloto, Emily Tagtow, Alan Black, Yiming Yang, Teruko Mitamura, Eduard Hovy' : '12 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">12 more authors</span> </div> <div class="periodical"> <em>Machine Translation</em>, Oct 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2018parser" class="col-sm-8"> <div class="title">Parser combinators for Tigrinya and Oromo morphology</div> <div class="author"> Patrick Littell, Tom McCoy, Na-Rae Han, and <span class="more-authors" title="click to view 5 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '5 more authors' ? 'Shruti Rijhwani, Zaid Sheikh, David Mortensen, Teruko Mitamura, Lori Levin' : '5 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">5 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 11th Language Resources and Evaluation Conference</em>, May 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018epitran" class="col-sm-8"> <div class="title">Epitran: Precision G2P for Many Languages</div> <div class="author"> David R. Mortensen, Siddharth Dalmia, and Patrick Littell </div> <div class="periodical"> <em>In Proceedings of the 11th Language Resources and Evaluation Conference</em>, May 2018 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018epitransw" class="col-sm-8"> <div class="title">Epitran</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> May 2018 </div> <div class="periodical"> Precision orthography-to-IPA conversion for 65 languages </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2018mstemsw" class="col-sm-8"> <div class="title">MStem</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> May 2018 </div> <div class="periodical"> Python multilingual morphological stemming framework and stemmer collection </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2017</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2017uriel" class="col-sm-8"> <div class="title">URIEL and lang2vec: Representing languages as typological, geographical, and phylogenetic vectors</div> <div class="author"> Patrick Littell, David R. Mortensen, Ke Lin, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Katherine Kairis, Carlisle Turner, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers</em>, Apr 2017 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>We introduce the URIEL knowledge base for massively multilingual NLP and thelang2vec utility, which provides information-rich vector identifications oflanguages drawn from typological, geographical, and phylogenetic databases andnormalized to have straightforward and consistent formats, naming, andsemantics. The goal of URIEL and lang2vec is to enable multilingual NLP,especially on less-resourced languages and make possible types of experiments(especially but not exclusively related to NLP tasks) that are otherwisedifficult or impossible due to the sparsity and incommensurability of the datasources. lang2vec vectors have been shown to reduce perplexity in multilinguallanguage modeling, when compared to one-hot language identification vectors.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2017hmong" class="col-sm-8"> <div class="title">Hmong-Mien Languages</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Oxford Research Encyclopedia of Linguistics</em>, May 2017 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2017hmongmienbib" class="col-sm-8"> <div class="title">Hmong-Mien Languages</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Oxford Bibliographies in Linguistics</em>, May 2017 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2016</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="bharadwaj2016phonologically" class="col-sm-8"> <div class="title">Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings</div> <div class="author"> Akash Bharadwaj, <em>David Mortensen</em>, Chris Dyer, and <span class="more-authors" title="click to view 1 more author" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '1 more author' ? 'Jaime Carbonell' : '1 more author'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">1 more author</span> </div> <div class="periodical"> <em>In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing</em>, Nov 2016 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2016bridge" class="col-sm-8"> <div class="title">Bridge-Language Capitalization Inference in Western Iranian: Sorani, Kurmanji, Zazaki, and Tajik</div> <div class="author"> Patrick Littell, David R. Mortensen, Kartik Goyal, and <span class="more-authors" title="click to view 2 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '2 more authors' ? 'Chris Dyer, Lori Levin' : '2 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">2 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)</em>, May 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>In Sorani Kurdish, one of the most useful orthographic features in named-entity recognition – capitalization – is absent, as the language’s Perso-Arabic script does not make a distinction between uppercase and lowercase letters. We describe a system for deriving an inferred capitalization value from closely related languages by phonological similarity, and illustrate the system using several related Western Iranian languages.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="littell2016named" class="col-sm-8"> <div class="title">Named Entity Recognition for Linguistic Rapid Response in Low-Resource Languages: Sorani Kurdish and Tajik</div> <div class="author"> Patrick Littell, Kartik Goyal, David R. Mortensen, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Alexa Little, Chris Dyer, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</em>, Dec 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper describes our construction of named-entity recognition (NER) systems in two Western Iranian languages, Sorani Kurdish and Tajik, as a part of a pilot study of “Linguistic Rapid Response” to potential emergency humanitarian relief situations. In the absence of large annotated corpora, parallel corpora, treebanks, bilingual lexica, etc., we found the following to be effective: exploiting distributional regularities in monolingual data, projecting information across closely related languages, and utilizing human linguist judgments. We show promising results on both a four-month exercise in Sorani and a two-day exercise in Tajik, achieved with minimal annotation costs.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2016panphon" class="col-sm-8"> <div class="title">PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors</div> <div class="author"> David R. Mortensen, Patrick Littell, Akash Bharadwaj, and <span class="more-authors" title="click to view 3 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '3 more authors' ? 'Kartik Goyal, Chris Dyer, Lori Levin' : '3 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">3 more authors</span> </div> <div class="periodical"> <em>In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</em>, Dec 2016 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> </div> <div class="abstract hidden"> <p>This paper contributes to a growing body of evidence that—when coupled with appropriate machine-learning techniques–linguistically motivated, information-rich representations can outperform one-hot encodings of linguistic data. In particular, we show that phonological features outperform character-based models. PanPhon is a database relating over 5,000 IPA segments to 21 subsegmental articulatory features. We show that this database boosts performance in various NER-related tasks. Phonologically aware, neural CRF models built on PanPhon features are able to perform better on monolingual Spanish and Turkish NER tasks that character-based models. They have also been shown to work well in transfer models (as between Uzbek and Turkish). PanPhon features also contribute measurably to Orthography-to-IPA conversion tasks.</p> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2016panphonsw" class="col-sm-8"> <div class="title">PanPhon</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Dec 2016 </div> <div class="periodical"> Articulatory feature extractor and library </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="tsvetkov2016polyglot" class="col-sm-8"> <div class="title">Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning</div> <div class="author"> Yulia Tsvetkov, Sunayana Sitaram, Manaal Faruqui, and <span class="more-authors" title="click to view 6 more authors" onclick=" var element=$(this); element.attr('title', ''); var more_authors_text=element.text() == '6 more authors' ? 'Guillaume Lample, Patrick Littell, David Mortensen, Alan W Black, Lori Levin, Chris Dyer' : '6 more authors'; var cursorPosition=0; var textAdder=setInterval(function(){ element.html(more_authors_text.substring(0, cursorPosition + 1)); if (++cursorPosition == more_authors_text.length){ clearInterval(textAdder); } }, '10'); ">6 more authors</span> </div> <div class="periodical"> <em>In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies</em>, Jun 2016 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2013</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2013lexical" class="col-sm-8"> <div class="title">Lexical Prefixes and Tibeto-Burman Laryngeal Contrasts</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the Thirty-Seventh Annual Meeting of the Berkeley Linguistics Society (BLS 37)</em>, Jun 2013 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2013reconstruction" class="col-sm-8"> <div class="title">A Reconstruction of Proto-Tangkhulic Rhymes</div> <div class="author"> David R. Mortensen, and James A. Miller </div> <div class="periodical"> <em>Linguistics of the Tibeto-Burman Area </em>, Jun 2013 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2013tonally" class="col-sm-8"> <div class="title">Tonally Conditioned Vowel Raising in Shuijingping Mang</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Journal of East Asian Linguistics</em>, Jun 2013 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2012</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2011sorbung" class="col-sm-8"> <div class="title">Sorbung, an Undescribed Language of Manipur: Its Phonology and Place in Tibeto-Burman</div> <div class="author"> David R. Mortensen, and Jennifer Keogh </div> <div class="periodical"> <em>Journal of the Southeast Asian Linguistics Society</em>, Jun 2012 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2012emergence" class="col-sm-8"> <div class="title">The Emergence of Obstruents after High Vowels</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Diachronica</em>, Jun 2012 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2012netspesw" class="col-sm-8"> <div class="title">NetSPE</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jun 2012 </div> <div class="periodical"> A web-based application for exploring rule-based analyses of phonological data </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="vercellotti2012classification" class="col-sm-8"> <div class="title">A Classification of Compounding in American Sign Language: an Evaluation of the Bisetto and Scalise Framework</div> <div class="author"> Mary Lou Vercellotti, and David R. Mortensen </div> <div class="periodical"> <em>Morphology</em>, Jun 2012 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2011</h2> <ol class="bibliography"> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2011hsspesw" class="col-sm-8"> <div class="title">HsSPE</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jun 2011 </div> <div class="periodical"> Haskell library implementing SPE-style rule-based phonology </div> <div class="links"> </div> </div> </div> </li> <li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2011webcomparatorsw" class="col-sm-8"> <div class="title">Web Comparator</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> Jun 2011 </div> <div class="periodical"> A web-based application for organizing and analyzing comparative lexical databases. Used in the production of “Emergence of Obstruents” and “Proto-Tangkhulic Rhymes” </div> <div class="links"> </div> </div> </div> </li> </ol> <h2 class="bibliography">2004</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2004emergence" class="col-sm-8"> <div class="title">The emergence of dorsal stops after high vowels in Huishu</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>In Proceedings of the Thirtieth Annual Meeting of the Berkeley Linguistics Society (BLS 30)</em>, Jun 2004 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> <h2 class="bibliography">2003</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen2003baheng" class="col-sm-8"> <div class="title">Review of \emphBaheng Yu Yanjiu [research on the Pa-Hng language] by Mao Zongwu and Li Yunbing</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Linguistics of the Tibeto-Burman Area</em>, Jun 2003 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> <h2 class="bibliography">2002</h2> <ol class="bibliography"><li> <div class="row"> <div class="col col-sm-2 abbr"> </div> <div id="mortensen20002langue" class="col-sm-8"> <div class="title">Review of \emphLes langue Hmong-Mjen: phonologie historique by Barbara Niederer</div> <div class="author"> David R. Mortensen </div> <div class="periodical"> <em>Linguistics of the Tibeto-Burman Area</em>, Jun 2002 </div> <div class="periodical"> </div> <div class="links"> </div> </div> </div> </li></ol> </div> </article> </div> </div> <footer class="fixed-bottom" role="contentinfo"> <div class="container mt-0"> © Copyright 2024 ChangeLing Lab. 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