Execute TwinMind primary workflow: Meeting transcription and summary generation.
Use when implementing meeting capture, building transcription features,
or automating meeting documentation.
Trigger with phrases like "twinmind transcription workflow",
"meeting transcription", "capture meeting with twinmind".
Primary workflow for capturing meetings, generating transcripts with speaker diarization, and creating AI summaries with action items.
Prerequisites
Completed twinmind-install-auth setup
TwinMind Pro/Enterprise for API access
Valid API credentials configured
Audio source available (live or file)
Instructions
Step 1: Initialize Meeting Capture
Build a MeetingCapture class with startLiveCapture() for real-time recording and for file-based transcription. Use Ear-3 model with auto language detection and speaker diarization.
transcribeRecording()
Step 2: Generate AI Summary
Create a SummaryGenerator with generateSummary() (brief/detailed/bullet-points formats), generateFollowUpEmail(), and generateMeetingNotes() methods.
Step 3: Handle Speaker Identification
Build a SpeakerManager that extracts speakers from transcript segments, calculates speaking time per speaker, and optionally matches speakers to calendar attendees.
Step 4: Orchestrate Complete Workflow
Wire everything together in processMeeting(): transcribe audio, then generate summary and identify speakers in parallel, optionally produce follow-up email and meeting notes.
See detailed implementation for complete MeetingCapture, SummaryGenerator, SpeakerManager, and orchestration code.
Output
Complete meeting transcript with timestamps
Speaker-labeled segments
AI-generated summary
Extracted action items with assignees
Optional follow-up email draft
Optional formatted meeting notes
Error Handling
Error
Cause
Solution
Transcription timeout
Large audio file
Increase maxWaitMs or use async callback
Speaker match failed
No calendar data
Provide attendees list manually
Summary generation failed
Transcript too short
Ensure minimum 30s of audio
Audio format unsupported
Wrong codec
Convert to MP3/WAV/M4A
Rate limit exceeded
Too many requests
Implement queue-based processing
Examples
Basic usage: Apply twinmind core workflow a to a standard project setup with default configuration options.
Advanced scenario: Customize twinmind core workflow a for production environments with multiple constraints and team-specific requirements.
Audio Format Support
Format
Supported
Notes
MP3
Yes
Recommended
WAV
Yes
Best quality
M4A
Yes
iOS recordings
WebM
Yes
Browser recordings
Resources
TwinMind Transcription API
Ear-3 Model Details
Audio Format Guide
Next Steps
For action item extraction and follow-up automation, see twinmind-core-workflow-b.
