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transcribe

@braselog/researchAssistant
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Transcribe audio files from meetings into text documents using Whisper. Use when the user types /transcribe, has a new audio recording, or when RA detects new audio files in meetings/audio/. Supports speaker diarization with pyannote.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name transcribe
description Transcribe audio files from meetings into text documents using Whisper. Use when the user types /transcribe, has a new audio recording, or when RA detects new audio files in meetings/audio/. Supports speaker diarization with pyannote.

Audio Transcription

Transcribe audio files from meetings into text documents.

Usage

/transcribe [filename]
/transcribe .research/meetings/audio/2024-12-02-lab-meeting.m4a
/transcribe .research/meetings/audio/  # Transcribe all untranscribed audio in directory

When to Use

  • After recording a meeting, seminar, or discussion
  • When RA detects new audio files in meetings/audio/ folder
  • Before running /summarize_meeting

Supported Formats

  • .m4a, .mp3, .wav, .webm, .mp4 (audio track)
  • .ogg, .flac

Execution

The command runs:

conda run -n research-assistant python .ra/skills/transcribe/scripts/transcribe.py [filename or .research/meetings/audio/]

Behavior:

  • If [filename] provided: transcribe that specific audio file
  • If no filename (or .research/meetings/audio/ specified): automatically detect all audio files without transcripts and process them
  • If transcript already exists for a file: skip it
  • Output saves to .research/meetings/transcripts/[same-name].md

Post-Transcription Options

Transcription complete! 

A) Run /summarize_meeting to extract action items and create tasks
B) Open transcript to review manually first
C) Continue with other work

What would you like to do?

Quality Notes

Improving Transcription Quality

  • Use good microphone/recording quality
  • Minimize background noise
  • Speak clearly and at moderate pace
  • Identify speakers at start if possible

Limitations

  • Speaker diarization may be imperfect
  • Technical terms may need manual correction
  • Timestamps are approximate

Configuration

Environment variables (optional):

  • WHISPER_MODEL: Model size (default: "small", options: tiny, base, small, medium, large-v3)
  • WHISPER_LANGUAGE: Force language (default: auto-detect)
  • HF_TOKEN: HuggingFace token for speaker diarization

Related Skills

  • summarize-meeting - Extract action items from transcript
  • next - Get next suggestion

Notes

  • Raw transcripts may contain errors - review before citing
  • Keep original audio files as source of truth
  • Transcripts are for internal use, not publication