Skill1.9k repo starsupdated 6d ago

whisper

The whisper skill converts audio files in formats including MP3, WAV, M4A, and FLAC into text transcriptions using OpenAI's Whisper model. Use this skill when you need to extract spoken content from audio recordings, supporting over 90 languages with optional timestamp generation and configurable model sizes ranging from tiny to large for different accuracy and speed tradeoffs.

View source Repository: trpc-agent-go

Install in Claude Code

Copy

git clone --depth 1 https://github.com/trpc-group/trpc-agent-go /tmp/whisper && cp -r /tmp/whisper/examples/skill/skills/whisper ~/.claude/skills/whisper

Then start a new Claude Code session; the skill loads automatically.

Definition

SKILL.md

# 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 json
```

## Parameters

- `audio_file` (required): Path to input audio file
- `output_file` (required): Path to output text/JSON file
- `--model`: Whisper model size (tiny/base/small/medium/large, default: base)
- `--language`: Language code (e.g., en, zh, es, fr, auto for detection)
- `--timestamps`: Include word-level timestamps in output
- `--format`: Output format (text/json, default: text)

## 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
```