grapheme-phoneme conversion and related stuff
gramophone is a package for hybrid grapheme-to-phoneme conversion using a set of heuristic mappings to determine admissible segmentations, a Conditional Random Field model for labelling candidate segmentations, and a language model over (grapheme,phoneme) segment-pairs to determine the optimal transcription.
We would appreciate gramophone users acknowledging its use in their publications. You can cite:
Kay-Michael Würzner & Bryan Jurish. "A hybrid approach to grapheme-phoneme conversion." In Proceedings of the 12th International Conference on Finite State Methods and Natural Language Processing (Düsseldorf, Germany, 22nd - 24th June, 2015), 2015.
The full paper can be downloaded here, and a BibTeX entry can be found here.
The gramophone package is distributed under the terms of the GNU Lesser General Public License (LGPL-v3), which itself incorporates the terms and conditions of the GNU General Public License.
gramophone is implemented in Python. In the following, we assume a working Python (Version ≥ 2.7, for Python 3: Version ≥ 3.4) installation as well as a working C++ compiler.
gramophone uses OpenFst for constructing and applying finite-state transducers. In particular, the Python interface is used. While the Python side can be installed via pip, the underlying C++ library has to be installed manually. The latest version of the Python interface available at the Python package index is 1.6.9. Obtain the corresponding sources from http://www.openfst.org/twiki/pub/FST/FstDownload/openfst-1.6.9.tar.gz and follow the instructions shipped with the package. Make sure to use the --enable-grm option while configuring.
Using virtualenv is highly recommended, although not strictly necessary for installing gramophone. It can be installed via:
$ [sudo] pip install virtualenvCreate a virtual environement in a subdirectory of your choice (e.g. env) using
$ virtualenv envand activate it.
$ . env/bin/activategramophone uses various 3rd party Python packages which may be best installed using pip:
(env) $ pip install -r requirements.txtFinally, you are ready to install the package:
(env) $ pip install -e .