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).
bash
# 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"
- •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