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Whisper Transcribe

Transcribe audio files to text using OpenAI Whisper. Supports speech-to-text with auto language detection, multiple output formats (txt, srt, vtt, json), batch processing, and model selection (tiny to large). Use when transcribing audio recordings, podcasts, voice messages, lectures, meetings, or any audio/video file to text. Handles mp3, wav, m4a, ogg, flac, webm, opus, aac formats.

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技能说明


name: whisper-transcribe description: Transcribe audio files to text using OpenAI Whisper. Supports speech-to-text with auto language detection, multiple output formats (txt, srt, vtt, json), batch processing, and model selection (tiny to large). Use when transcribing audio recordings, podcasts, voice messages, lectures, meetings, or any audio/video file to text. Handles mp3, wav, m4a, ogg, flac, webm, opus, aac formats.

Whisper Transcribe

Transcribe audio with scripts/transcribe.sh:

# Basic (auto-detect language, base model)
scripts/transcribe.sh recording.mp3

# German, small model, SRT subtitles
scripts/transcribe.sh --model small --language de --format srt lecture.wav

# Batch process, all formats
scripts/transcribe.sh --format all --output-dir ./transcripts/ *.mp3

# Word-level timestamps
scripts/transcribe.sh --timestamps interview.m4a

Models

ModelRAMSpeedAccuracyBest for
tiny~1GB⚡⚡⚡★★Quick drafts, known language
base~1GB⚡⚡★★★General use (default)
small~2GB★★★★Good accuracy
medium~5GB🐢★★★★★High accuracy
large~10GB🐌★★★★★Best accuracy (slow on Pi)

Output Formats

  • txt — Plain text transcript
  • srt — SubRip subtitles (for video)
  • vtt — WebVTT subtitles
  • json — Detailed JSON with timestamps and confidence
  • all — Generate all formats at once

Requirements

  • whisper CLI (pip install openai-whisper)
  • ffmpeg (for audio decoding)
  • First run downloads the model (~150MB for base)

如何使用「Whisper Transcribe」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Whisper Transcribe技能完成任务
  4. 结果即时呈现,支持继续对话优化

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