meeting-transcription

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Transcribe audio recordings from meetings (MP3, WAV, M4A) into text using AWS Transcribe service

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[Meeting Productivity]

When & Why to Use This Skill

The Meeting Transcription skill automates the conversion of audio recordings into accurate, speaker-labeled text using AWS Transcribe. It supports a wide range of formats including MP3, WAV, and M4A across multiple languages. By transforming raw audio into structured transcripts, it enables Claude to perform deep analysis on meeting content, such as extracting action items, summarizing key discussion points, and evaluating participant engagement.

Use Cases

  • Automated Meeting Minutes: Transcribe team syncs or 1:1 recordings to quickly generate summaries and track assigned tasks.
  • Speaker Identification & Analysis: Utilize speaker labels to analyze conversation flow, speaking balance, and communication patterns in multi-person interviews.
  • Multi-language Documentation: Convert international meeting recordings into text with support for English, Chinese, Spanish, French, German, and more.
  • Searchable Audio Archives: Transform voice memos and recorded discussions into a searchable text database for efficient knowledge management and retrieval.
nameMeeting Transcription
descriptionTranscribe audio recordings from meetings (MP3, WAV, M4A) into text using AWS Transcribe service

Meeting Transcription Skill

This skill enables transcription of meeting audio files to text using AWS Transcribe.

When to Use This Skill

Use this skill when the user:

  • Provides an audio recording of a meeting
  • Asks to transcribe a meeting
  • Wants to analyze meeting content from an audio file
  • Mentions audio files with extensions like .mp3, .wav, .m4a, .mp4, .flac

How It Works

  1. User provides path to an audio file
  2. This skill calls the transcribe_audio.py script with optional language parameter
  3. The script uploads audio to S3 and uses AWS Transcribe
  4. Returns the full transcript as plain text with speaker labels (if applicable)
  5. You (the agent) can then analyze the transcript

Usage

IMPORTANT: Always specify the language to get speaker labels (spk_0, spk_1).

# English meeting (default)
python transcribe_audio.py /path/to/audio.mp3

# Chinese meeting
python transcribe_audio.py /path/to/audio.mp3 --language zh-CN

# Other languages
python transcribe_audio.py /path/to/audio.mp3 --language es-ES

Supported Languages:

  • en-US: English (US) - default
  • zh-CN: Mandarin Chinese (Simplified)
  • zh-TW: Traditional Chinese (Taiwan)
  • es-ES: Spanish (Spain)
  • fr-FR: French
  • de-DE: German
  • ja-JP: Japanese
  • ko-KR: Korean

Speaker Labels: All transcriptions include speaker labels (spk_0, spk_1, spk_2, etc.) to identify different speakers in the conversation. You must know the language beforehand.

Supported Audio Formats

  • MP3
  • MP4
  • WAV
  • FLAC
  • M4A
  • OGG
  • WebM

Usage Example

When the user says: "Analyze my 1:1 meeting recording at ./recordings/meeting.mp3"

  1. Use this skill to transcribe the audio first
  2. Once you have the transcript, analyze it for insights
  3. Provide actionable feedback to the user

What to Do After Transcription

After getting the transcript, analyze it for:

  • Key discussion topics: What were the main themes?
  • Action items: What tasks were assigned or agreed upon?
  • Speaking balance: Who spoke more? Is it balanced?
  • Questions: What questions were asked? Were they answered?
  • Communication patterns: Any interruptions, pauses, or unclear moments?
  • Tone and engagement: Is the conversation collaborative or one-sided?
  • Constructive feedback: What could be improved for next time?

Technical Details

  • Requires AWS credentials configured
  • Requires S3 bucket for temporary audio storage
  • Audio files are automatically cleaned up after transcription
  • Transcription job names are timestamped to avoid conflicts