📃: Added TextToTalk - A text to speech project (#318)

# Pull Request for PyVerse 💡


## Issue Title : 📃: Adding Text to Speech Machine Learning project in
the Machine_Learning directory #303

- **Info about the related issue (Aim of the project)** : To get to know
the T2S
- **Name:** Tejas
- **GitHub ID:**  @LitZeus
- **Email ID:** [email protected]
- **Idenitfy yourself:** Participating as a `GSSoc-extd | Contributor` ,
`Hacktoberfest`


Closes: #303 

### Added a Text to Speech converter 

Introducing a Streamlit web app that enables users to upload a PDF file
and convert its text content into an MP3 audio file. It uses
pdfminer.six for extracting text and gtts (Google Text-to-Speech) for
audio conversion, providing a simple interface to make written content
accessible through speech.

## Type of change ☑️

What sort of change have you made:
<!--
Example how to mark a checkbox:-
- [x] My code follows the code style of this project.
-->
- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [ ] Code style update (formatting, local variables)
- [ ] Breaking change (fix or feature that would cause existing
functionality to not work as expected)
- [ ] This change requires a documentation update

## How Has This Been Tested? ⚙️

It has been tested by me in my local machine and also hosted on
Streamlit without any errors and conflicts

## Checklist: ☑️
<!--
Example how to mark a checkbox:-
- [x] My code follows the code style of this project.
-->
- [x] My code follows the guidelines of this project.
- [x] I have performed a self-review of my own code.
- [x] I have commented my code, particularly wherever it was hard to
understand.
- [x] I have made corresponding changes to the documentation.
- [x] My changes generate no new warnings.
- [x] I have added things that prove my fix is effective or that my
feature works.
- [x] Any dependent changes have been merged and published in downstream
modules.

Machine_Learning/TextToTalk/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 Tejas Athalye
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

Machine_Learning/TextToTalk/README.md

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+# TextToTalk: A PDF to MP3 Converter Web App
+
+This is a Streamlit-based web application that allows users to upload a PDF file and convert its text content to an MP3 audio file. The application uses `pdfminer.six` for extracting text from the PDF and `gtts` (Google Text-to-Speech) for converting text to speech.
+
+## Features
+
+- Upload a PDF file using a drag-and-drop interface or a file upload button.
+- Select the desired language for text-to-speech conversion.
+- Convert the text content of the PDF to an MP3 audio file.
+- Play the generated audio file directly on the web app.
+- Download the generated audio file.
+
+## Requirements
+
+- `Python 3.6 or higher`
+- `pdfminer.six`
+- `gtts`
+- `streamlit`
+
+## Installation
+
+#### First Fork the repository and then follow the steps given below!
+
+1. Clone the repository in your local machine:
+   ```sh
+   git clone https://github.com/<your-username>/PyVerse.git
+   cd Machine_Learning/TextToTalk
+   ```
+
+2. Create a virtual environment:
+   ```sh
+   python -m venv venv
+   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
+   ```
+
+3. Install the required packages:
+   ```sh
+   pip install -r requirements.txt
+   ```
+
+## Usage
+
+  1. Run the Streamlit app:
+     ```sh
+     cd scripts
+     streamlit run app.py
+     ```
+
+  2. Open your web browser and go to `http://localhost:8501` to access the app.
+
+  3. Upload a PDF file using the provided upload button or drag and drop the file into the designated area.
+
+  4. Select the desired language for the text-to-speech conversion.
+
+  5. The app will extract the text from the uploaded PDF, convert it to speech, and display an audio player for you to listen to the generated MP3 file.
+
+  6. You can also download the generated MP3 file using the download button.
+
+## File Structure
+- `ExtText.py`: Contains the function for extracting text from the uploaded PDF file using pdfminer.six.
+- `TTS.py`: Contains the function for converting text to speech using gtts.
+- `Pipeline.py`: Integrates the text extraction and text-to-speech conversion functions into a single pipeline.
+- `app.py`: The main Streamlit app that provides the web interface for the PDF to MP3 conversion.
+
+## Contributing
+Contributions are welcome! If you find any bugs or have suggestions for improvements, please open an issue or create a pull request.
+
+## License
+This project is licensed under the MIT License. See the `LICENSE` file for more details.
+

Machine_Learning/TextToTalk/requirements.txt

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+pdfminer.six
+gtts
+streamlit

Machine_Learning/TextToTalk/scripts/ExtText.py

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+from io import BytesIO
+from pdfminer.high_level import extract_text_to_fp
+from pdfminer.layout import LAParams
+
+def extract_text(uploaded_file):
+    """Extracts text from the uploaded PDF file using pdfminer.six."""
+    if not uploaded_file:
+        return None
+
+    try:
+        output_string = BytesIO()
+        laparams = LAParams()
+        extract_text_to_fp(uploaded_file, output_string, laparams=laparams)
+        return output_string.getvalue().decode('utf-8')
+    except Exception as e:
+        print(f"Error extracting text: {e}")
+        return None

Machine_Learning/TextToTalk/scripts/Pipeline.py

@@ -0,0 +1,10 @@
+from ExtText import extract_text
+from TTS import text_to_speech
+
+def pipeline(uploaded_file, lang='en'):
+    """Extracts text and converts it to speech in a pipeline."""
+    extracted_text = extract_text(uploaded_file)
+    if extracted_text:
+        return text_to_speech(extracted_text, lang=lang)
+    else:
+        return None

Machine_Learning/TextToTalk/scripts/TTS.py

@@ -0,0 +1,17 @@
+from gtts import gTTS
+from io import BytesIO
+
+def text_to_speech(text, lang='en'):
+    """Converts the extracted text to audio (MP3) using gTTS."""
+    if not text:
+        return None
+
+    try:
+        tts = gTTS(text=text, lang=lang)
+        audio_file = BytesIO()
+        tts.write_to_fp(audio_file)
+        audio_file.seek(0)
+        return audio_file
+    except Exception as e:
+        print(f"Error generating audio: {e}")
+        return None

Machine_Learning/TextToTalk/scripts/app.py

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+import streamlit as st
+from Pipeline import pipeline
+
+def main():
+    """Streamlit app for PDF to MP3 conversion."""
+    st.title("PDF to MP3 Converter")
+
+    uploaded_file = st.file_uploader("Choose a PDF file to convert:", type=['pdf'])
+
+    if uploaded_file is not None:
+        audio_file = pipeline(uploaded_file, lang=lang_code)
+        if audio_file:
+            st.audio(audio_file, format='audio/mp3')
+            st.download_button(
+                label="Download Audio",
+                data=audio_file,
+                file_name="output.mp3",
+                mime="audio/mp3"
+            )
+        else:
+            st.error("Failed to convert PDF to audio.")
+
+if __name__ == '__main__':
+    main()