Real Time Speech To Text (Using OpenAi Whisper)

Requirements

• Python 3.1x

Setting Up

• Install requirements using pip install -r requirements.txt

Running the Application

• Run the flask app using python3 app.py

Selecting the Appropriate Model

Whisper offers several models that balance speed and accuracy:

• tiny: Fastest but least accurate
• base: A balance between speed and accuracy
• small: More accurate, slower than base
• medium: Even more accurate, slower than small
• large: Most accurate but slowest

You can select a model by specifying it when loading the Whisper model. For example:

self.model = whisper.load_model("medium")

Demo

To-Dos

• Improve accuracy of transcription
• Add support for multiple languages
• Optimize performance for low-latency environments
• Implement speaker recognition
• Webohook - Create separate sessions(?) for each connected client

Contribution Guidelines

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add new feature').
5. Push to the branch (git push origin feature-branch).
6. Create a pull request.

License

This project is licensed under the MIT License.