whisper
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Transcribe audio files to text using OpenAI Whisper
7installs
Sourcetrpc-group/trpc-agent-go
Added on
NPX Install
npx skill4agent add trpc-group/trpc-agent-go whisperTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →Whisper Audio Transcription Skill
Transcribe audio files to text using OpenAI Whisper.
Capabilities
- Transcribe audio files (MP3, WAV, M4A, FLAC, OGG, etc.) to text
- Support for 90+ languages with auto-detection
- Optional timestamp generation
- Multiple model sizes (tiny/base/small/medium/large)
- Output in plain text or JSON format
Usage
Basic Transcription
bash
python3 scripts/transcribe.py <audio_file> <output_file>With Options
bash
# Specify model size (default: base)
python3 scripts/transcribe.py audio.mp3 transcript.txt --model medium
# Specify language (improves accuracy)
python3 scripts/transcribe.py audio.mp3 transcript.txt --language zh
# Include timestamps
python3 scripts/transcribe.py audio.mp3 transcript.txt --timestamps
# JSON output with metadata
python3 scripts/transcribe.py audio.mp3 output.json --format jsonParameters
- (required): Path to input audio file
audio_file - (required): Path to output text/JSON file
output_file - : Whisper model size (tiny/base/small/medium/large, default: base)
--model - : Language code (e.g., en, zh, es, fr, auto for detection)
--language - : Include word-level timestamps in output
--timestamps - : Output format (text/json, default: text)
--format
Model Sizes
| Model | Parameters | Speed | Accuracy | Memory |
|---|---|---|---|---|
| tiny | 39M | ~32x | Good | ~1GB |
| base | 74M | ~16x | Better | ~1GB |
| small | 244M | ~6x | Great | ~2GB |
| medium | 769M | ~2x | Excellent | ~5GB |
| large | 1.5B | 1x | Best | ~10GB |
Supported Audio Formats
MP3, WAV, M4A, FLAC, OGG, AAC, WMA, and more (via FFmpeg)
Dependencies
- Python 3.8+
- openai-whisper
- ffmpeg
Installation
bash
pip install openai-whisper
sudo apt-get install ffmpeg # Ubuntu/Debian