Multi-Speaker Recognition and Summarization System
AI-powered Meeting Analysis Solution
Duration
4 months
Status
Completed
Team
Team
Type
AI/ML
Project Overview
Developed an AI system that detects and recognizes multiple speakers in group discussions and creates automated summaries.
Detailed Description
This advanced audio processing system automatically transcribes group discussions, identifies individual speakers, and generates concise summaries of conversations.
Key achievements: - Implemented speaker diarization to identify 10+ speakers simultaneously - Built transcription system with 95%+ accuracy - Created intelligent summarization engine capturing key points - Reduced meeting documentation time by 80%
The system is valuable for meeting analysis, collaboration tracking, and automatic documentation generation.
Challenge
Accurately separating overlapping speech from multiple speakers.
Solution
Used advanced neural network architectures for robust speaker separation and identification.
Technologies & Skills
Interested in this project?
Get in touch to learn more about my work or discuss collaboration opportunities.
Get in Touch