| name | Meeting Transcription |
| description | Transcribe 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
- User provides path to an audio file
- This skill calls the
transcribe_audio.pyscript with optional language parameter - The script uploads audio to S3 and uses AWS Transcribe
- Returns the full transcript as plain text with speaker labels (if applicable)
- 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) - defaultzh-CN: Mandarin Chinese (Simplified)zh-TW: Traditional Chinese (Taiwan)es-ES: Spanish (Spain)fr-FR: Frenchde-DE: Germanja-JP: Japaneseko-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"
- Use this skill to transcribe the audio first
- Once you have the transcript, analyze it for insights
- 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