🎙️ Faster Whisper GPU

High-performance local speech-to-text transcription using Faster Whisper with NVIDIA GPU acceleration.

✨ Features

• 🚀 GPU Accelerated: Uses NVIDIA CUDA for blazing-fast transcription
• 🔒 100% Local: No data leaves your machine. Complete privacy.
• 💰 Free Forever: No API costs. Run unlimited transcriptions.
• 🌍 Multilingual: Supports 99 languages with automatic detection
• 📁 Multiple Formats: Input: MP3, WAV, FLAC, OGG, M4A. Output: TXT, SRT, JSON
• 🎯 Multiple Models: From tiny (fast) to large-v3 (most accurate)
• 🎬 Subtitle Generation: Create SRT files with word-level timestamps

📋 Requirements

Hardware

• NVIDIA GPU with CUDA support (recommended: 4GB+ VRAM)
• Or CPU-only mode (slower but works on any machine)

Software

• Python 3.8+
• NVIDIA drivers (for GPU support)
• CUDA Toolkit 11.8+ or 12.x

🚀 Quick Start

Installation

# Install dependencies
pip install faster-whisper torch

# Verify GPU is available
python -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}')"

Basic Usage

# Transcribe an audio file (auto-detects GPU)
python transcribe.py audio.mp3

# Specify language explicitly
python transcribe.py audio.mp3 --language pt

# Output as SRT subtitles
python transcribe.py audio.mp3 --format srt --output subtitles.srt

# Use larger model for better accuracy
python transcribe.py audio.mp3 --model large-v3

🔧 Advanced Usage

Command Line Options

python transcribe.py <audio_file> [options]

Options:
  --model {tiny,base,small,medium,large-v1,large-v2,large-v3}
                        Model size to use (default: base)
  --language LANG       Language code (e.g., 'pt', 'en', 'es'). Auto-detect if not specified.
  --format {txt,srt,json,vtt}
                        Output format (default: txt)
  --output FILE         Output file path (default: stdout)
  --device {cuda,cpu}   Device to use (default: cuda if available)
  --compute_type {int8,int8_float16,int16,float16,float32}
                        Computation precision (default: float16)
  --task {transcribe,translate}
                        Task: transcribe or translate to English (default: transcribe)
  --vad_filter          Enable voice activity detection filter
  --vad_parameters MIN_DURATION_ON,MIN_DURATION_OFF
                        VAD parameters as comma-separated values
  --condition_on_previous_text
                        Condition on previous text (default: True)
  --initial_prompt PROMPT
                        Initial prompt to guide transcription
  --word_timestamps     Include word-level timestamps (for SRT/JSON)
  --hotwords WORDS      Comma-separated hotwords to boost recognition

Examples

Portuguese Transcription with SRT Output

python transcribe.py meeting.mp3 --language pt --format srt --output meeting.srt