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@ -6,7 +6,7 @@ This project extends the [Whisper Streaming](https://github.com/ufal/whisper_str
2. **Buffering Indication**: Improves streaming display by showing the current processing status, providing users with immediate feedback. 2. **Buffering Indication**: Improves streaming display by showing the current processing status, providing users with immediate feedback.
3. **Javascript Client implementation**: Functionnal and minimalist MediaRecorder implementation that can be copied on your client side 3. **Javascript Client implementation**: Functionnal and minimalist MediaRecorder implementation that can be copied on your client side.
4. **MLX Whisper backend**: Integrates the alternative backend option MLX Whisper, optimized for efficient speech recognition on Apple silicon. 4. **MLX Whisper backend**: Integrates the alternative backend option MLX Whisper, optimized for efficient speech recognition on Apple silicon.
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### How to Launch the Server ### How to Launch the Server
1. **Install Dependencies**: 1. **Dependencies**:
- Install required dependences :
```bash ```bash
pip install -r requirements.txt # Whisper streaming required dependencies
pip install librosa soundfile
# Whisper streaming web required dependencies
pip install fastapi ffmpeg
``` ```
2. Install a whisper backend among: - Install at least one whisper backend among:
``` ```
whisper whisper
whisper-timestamped whisper-timestamped
faster-whisper (faster backend on NVIDIA GPU) faster-whisper (faster backend on NVIDIA GPU)
mlx-whisper (faster backend on Apple Silicon) mlx-whisper (faster backend on Apple Silicon)
and torch if you want to use VAC (Voice Activity Controller)
```
- Optionnal dependencies
and torch if you want to use VAC (Voice Activity Controller) ```
``` # If you want to use VAC (Voice Activity Controller)
torch
# If you choose sentences as buffer trimming strategy
mosestokenizer
wtpsplit
tokenize_uk # If you work with Ukrainian text
# If you want to run the server using uvicorn (recommended)
uvicorn
```
3. **Run the FastAPI Server**: 3. **Run the FastAPI Server**: