faster-whisper

# Faster-Whisper High-performance local speech-to-text using faster-whisper. ## Setup ### 1. Run Setup Script Execute the setup script to create a virtual environment and install dependencies. It will automatically detect NVIDIA GPUs for CUDA acceleration. ```bash ./setup.sh ``` Requirements: - Python 3.10 or later - ffmpeg (installed on the system) ## Usage Use the transcription script to process audio files. ### Basic Transcription ```bash ./scripts/transcribe audio.mp3 ``` ### Advanced Options - **Specific Model**: `./scripts/transcribe audio.mp3 --model large-v3-turbo` - **Word Timestamps**: `./scripts/transcribe audio.mp3 --word-timestamps` - **JSON Output**: `./scripts/transcribe audio.mp3 --json` - **VAD (Silence Removal)**: `./scripts/transcribe audio.mp3 --vad` ## Available Models - `distil-large-v3` (default): Best balance of speed and accuracy. - `large-v3-turbo`: Recommended for multilingual or highest accuracy tasks. - `medium.en`, `small.en`: Faster, English-only versions. ## Troubleshooting - **No GPU detected**: Ensure NVIDIA drivers and CUDA are correctly installed. CPU transcription is significantly slower. - **OOM Error**: Use a smaller model (e.g., `small` or `base`) or use `--compute-type int8`.