ThiThanhChuong/precision-voice

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. 1.Docker and Docker Compose
2. 2.(Optional) NVIDIA GPU with CUDA support
3. 3.HuggingFace account with access to pyannote models

Setup

1. 1.Clone and configure:

   cp .env.example .env
   # Edit .env and add your HuggingFace token

1. 1.Build and run:

   docker compose up --build

1. 1.Open http://localhost:8000

Audio Processing Pipeline

The system uses a state-of-the-art multi-stage pipeline to ensure maximum accuracy:

1. 1.Speech Enhancement: Background noise and reverb are removed using SpeechBrain SepFormer (DNS4 Challenge winner).
2. 2.Vocal Isolation: Vocals are separated from background music using MDX-Net.
3. 3.VAD Filtering: Silence is removed using Silero VAD v5 to prevent ASR hallucination.
4. 4.Refinement: Highpass filtering and EBU R128 loudness normalization.
5. 5.Transcription: High-precision Vietnamese transcription using PhoWhisper.
6. 6.Diarization: Segmenting audio by speaker using Pyannote 3.1.
7. 7.Alignment: Merging transcripts with speaker segments + timestamp reconstruction.

Configuration

Development

Local Setup (without Docker)

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload

API Endpoints

Supported Audio Formats

• —MP3
• —WAV
• —M4A
• —OGG

License

MIT