🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
BytesAgain β€Ί Skills β€Ί Whisper STT
πŸ¦€ ClawHub

Whisper STT

by @nickylin

Free local speech-to-text transcription using OpenAI Whisper. Transcribe audio files (mp3, wav, m4a, ogg, etc.) to text without API costs. Use when: (1) User...

Versionv1.0.0
Downloads1,761
Installs15
#writing#video#audio#legal#communication
TERMINAL
clawhub install whisper-stt

πŸ“– About This Skill

name: whisper-stt description: | Free local speech-to-text transcription using OpenAI Whisper. Transcribe audio files (mp3, wav, m4a, ogg, etc.) to text without API costs. Use when: (1) User needs audio/video transcription, (2) Converting voice memos to text, (3) Generating subtitles (SRT/VTT), (4) Free local STT without cloud API costs.

Whisper STT Skill

Free, local speech-to-text using OpenAI Whisper.

Prerequisites

Install dependencies (one-time setup):

pip install openai-whisper torch

Optional: Install ffmpeg for broader format support:

  • macOS: brew install ffmpeg
  • Ubuntu: sudo apt install ffmpeg

    • Usage

    Transcribe an audio file

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py

    Options

    | Option | Description | |--------|-------------| | --model | Model size: tiny, base, small, medium, large, large-v3-turbo (default: base) | | --language, -l | Language code: zh, en, ja, etc. (auto-detect if not specified) | | --output, -o | Output format: json, txt, srt, vtt (default: json) |

    Examples

    Chinese audio to text: 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py recording.m4a --language zh --output txt

    Generate subtitles (SRT): 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py video.mp4 --output srt > subtitles.srt

    Use faster model: 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model tiny --output txt

    High accuracy (slower): 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model large-v3 --output txt

    Model Selection Guide

    | Model | Speed | Accuracy | VRAM/RAM | Best For | |-------|-------|----------|----------|----------| | tiny | ~32x | Basic | ~1GB | Quick tests, low resource | | base | ~16x | Good | ~1GB | Balanced speed/accuracy | | small | ~6x | Better | ~2GB | Better accuracy | | medium | ~2x | Very Good | ~5GB | High accuracy | | large | 1x | Excellent | ~10GB | Best quality | | large-v3-turbo | ~8x | Excellent | ~6GB | Fast + accurate (recommended) |

    Troubleshooting

    "ModuleNotFoundError: No module named 'whisper'" β†’ Run: pip install openai-whisper torch

    "ffmpeg not found" β†’ Install ffmpeg or convert audio to WAV format first

    Slow transcription β†’ Use smaller model (tiny/base) or ensure GPU is available (Apple Silicon MPS, NVIDIA CUDA)

    Poor accuracy on Chinese β†’ Use --language zh explicitly and consider larger model (medium/large)

    Output Formats

  • json: Full result with segments, timestamps, and metadata
  • txt: Plain text transcription only
  • srt: SubRip subtitle format with timing
  • vtt: WebVTT subtitle format for web players

    • Credits

    Powered by OpenAI Whisper - open source speech recognition.

    πŸ’‘ Examples

    Chinese audio to text: 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py recording.m4a --language zh --output txt

    Generate subtitles (SRT): 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py video.mp4 --output srt > subtitles.srt

    Use faster model: 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model tiny --output txt

    High accuracy (slower): 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model large-v3 --output txt

    βš™οΈ Configuration

    | Option | Description | |--------|-------------| | --model | Model size: tiny, base, small, medium, large, large-v3-turbo (default: base) | | --language, -l | Language code: zh, en, ja, etc. (auto-detect if not specified) | | --output, -o | Output format: json, txt, srt, vtt (default: json) |

    Examples

    Chinese audio to text: 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py recording.m4a --language zh --output txt

    Generate subtitles (SRT): 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py video.mp4 --output srt > subtitles.srt

    Use faster model: 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model tiny --output txt

    High accuracy (slower): 

    python ~/.openclaw/skills/whisper-stt/scripts/transcribe.py audio.mp3 --model large-v3 --output txt

    πŸ“‹ Tips & Best Practices

    "ModuleNotFoundError: No module named 'whisper'" β†’ Run: pip install openai-whisper torch

    "ffmpeg not found" β†’ Install ffmpeg or convert audio to WAV format first

    Slow transcription β†’ Use smaller model (tiny/base) or ensure GPU is available (Apple Silicon MPS, NVIDIA CUDA)

    Poor accuracy on Chinese β†’ Use --language zh explicitly and consider larger model (medium/large)