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| title: PrecisionVoice | |
| emoji: 🎙️ | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: docker | |
| app_file: app/main.py | |
| pinned: false | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| # PrecisionVoice - STT & Speaker Diarization | |
| A production-ready Speech-to-Text and Speaker Diarization web application using FastAPI, faster-whisper, and pyannote.audio. | |
| ## Features | |
| - 🎙️ Speech-to-Text using `erax-ai/EraX-WoW-Turbo-V1.1-CT2` (8x faster, 8 Vietnamese dialects) | |
| - 👥 Speaker Diarization using `pyannote/speaker-diarization-3.1` | |
| - 🧼 Speech Enhancement using `SpeechBrain SepFormer DNS4` (noise + reverb removal) | |
| - 🔇 Voice Activity Detection using `Silero VAD v5` (prevents hallucination) | |
| - 🎤 Vocal Isolation using `MDX-Net` (UVR-MDX-NET-Voc_FT) | |
| - 🔄 Automatic speaker-transcript alignment | |
| - 📥 Download results in TXT or SRT format | |
| - 🐳 Docker-ready with persistent model caching and GPU support | |
| - 🐳 Docker-ready with persistent model caching and GPU support | |
| ## Quick Start | |
| ### Prerequisites | |
| 1. Docker and Docker Compose | |
| 2. (Optional) NVIDIA GPU with CUDA support | |
| 3. HuggingFace account with access to pyannote models | |
| ### Setup | |
| 1. Clone and configure: | |
| ```bash | |
| cp .env.example .env | |
| # Edit .env and add your HuggingFace token | |
| ``` | |
| 2. Build and run: | |
| ```bash | |
| docker compose up --build | |
| ``` | |
| 3. Open http://localhost:8000 | |
| ## Audio Processing Pipeline | |
| The system uses a state-of-the-art multi-stage pipeline to ensure maximum accuracy: | |
| 1. **Speech Enhancement**: Background noise and reverb are removed using `SpeechBrain SepFormer` (DNS4 Challenge winner). | |
| 2. **Vocal Isolation**: Vocals are separated from background music using `MDX-Net`. | |
| 3. **VAD Filtering**: Silence is removed using `Silero VAD v5` to prevent ASR hallucination. | |
| 4. **Refinement**: Highpass filtering and EBU R128 loudness normalization. | |
| 5. **Transcription**: High-precision Vietnamese transcription using `PhoWhisper`. | |
| 6. **Diarization**: Segmenting audio by speaker using `Pyannote 3.1`. | |
| 7. **Alignment**: Merging transcripts with speaker segments + timestamp reconstruction. | |
| ## Configuration | |
| | Variable | Default | Description | | |
| |----------|---------|-------------| | |
| | `HF_TOKEN` | - | Required for Pyannote models | | |
| | `ENABLE_SPEECH_ENHANCEMENT` | `True` | Toggle SpeechBrain speech enhancement | | |
| | `ENHANCEMENT_MODEL` | `speechbrain/sepformer-dns4-16k-enhancement` | Model for speech enhancement | | |
| | `ENABLE_SILERO_VAD` | `True` | Toggle Silero VAD for hallucination prevention | | |
| | `ENABLE_VOCAL_SEPARATION` | `True` | Toggle MDX-Net vocal isolation | | |
| | `MDX_MODEL` | `UVR-MDX-NET-Voc_FT` | Model for vocal separation | | |
| | `DEVICE` | `auto` | `cuda`, `cpu`, or `auto` | | |
| ## Development | |
| ### Local Setup (without Docker) | |
| ```bash | |
| python -m venv venv | |
| source venv/bin/activate | |
| pip install -r requirements.txt | |
| uvicorn app.main:app --reload | |
| ``` | |
| ### API Endpoints | |
| | Endpoint | Method | Description | | |
| |----------|--------|-------------| | |
| | `/` | GET | Web UI | | |
| | `/api/transcribe` | POST | Upload and transcribe audio | | |
| | `/api/download/{filename}` | GET | Download result files | | |
| ## Supported Audio Formats | |
| - MP3 | |
| - WAV | |
| - M4A | |
| - OGG | |
| ## License | |
| MIT | |