TwinMind Core Workflow A: Meeting Transcription & Summary

Contents

• Overview
• Prerequisites
• Instructions
• Output
• Error Handling
• Examples
• Resources

Overview

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

transcribeRecording()

for file-based transcription. Use Ear-3 model with auto language detection and speaker diarization.

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

.