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Whisper STT

基于 OpenAI Whisper 的本地语音转文字 Skill,通过 transcribe.py 把 mp3/wav/m4a/ogg、视频等音频转为文本或字幕,支持 json/txt/srt/vtt 输出、模型尺寸与语言参数选择,无需云端 API。

nickylin
nickylin
热度 86.25
最近更新 2026-05-11 17:27:40
分类:效率依赖:代码执行 / 读写文件应用场景:文件转换 / 数据处理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add whisper-stt
Metadata
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 <audio_file>

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'" → Run: pip install openai-whisper torch

"ffmpeg not found" → Install ffmpeg or convert audio to WAV format first

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

Poor accuracy on Chinese → 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.