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

python3 scripts/transcribe.py <audio_file> <output_file>

With Options

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

pip install openai-whisper sudo apt-get install ffmpeg # Ubuntu/Debian