- Speech-to-Text (STT): Real-time transcription of spoken language.
- Text-to-Speech (TTS): Convert entered text into synthesized speech.
- Azure Speech SDK: Utilizes Azure Cognitive Services for speech-related tasks.
- Streamlit: Provides a user-friendly web interface for interacting with the Azure Speech Services.
- Clone the repository:
git clone https://github.com/Sgvkamalakar/Azure_AI_Speech_Services
- Install dependencies
pip install -r requirements.txt
- Set up Azure Speech API key and service region:
- Create a .env file based on the provided .env.sample.
- Add your Azure Speech API key and service region to the .env file.
- Run the application:
streamlit run app.py
- Speech-to-Text (STT): Click on "Start Transcription" to transcribe real-time audio.
- Text-to-Speech (TTS): Enter text in the provided text area and click "Generate Speech" to synthesize speech.
We welcome contributions from the community! If you'd like to contribute to the development of Azure Speech Services with Streamlit, please follow these steps:
- Fork the repository.
- Create a new branch:
git checkout -b feature/new-feature
. - Make your changes and commit:
git commit -m 'Add new feature'
. - Push to the branch:
git push origin feature/new-feature
. - Submit a pull request.
- The application is designed with a user-friendly interface, allowing users to choose between Speech-to-Text and Text-to-Speech functionalities.
- Real-time audio transcription is supported for Speech-to-Text.
- The project is structured for easy integration and further development.