Abstract

A system and method for automated multi-speaker identification and selective audio processing in research environments addresses the challenge of capturing, analyzing, and managing multi-speaker conversations with privacy protections and minimal manual intervention. The system comprises a microphone array (100) with central omnidirectional and distributed directional microphones positioned at known spatial coordinates, a spatial localization processor (110) triangulating speaker positions using time-of-arrival analysis, an audio fingerprinting module (120) generating session-ephemeral acoustic fingerprints for persistent speaker identification without cross-session tracking, a selective processing module (130) enforcing consent-based filtering through exclusion, anonymization, or pseudonymization modes, a speech separation engine (140) isolating individual contributions from overlapping audio using spatial and acoustic correlation, a speech recognition module (150) generating speaker-attributed transcripts, a semantic analysis engine (160) detecting linguistic markers of learning, engagement, knowledge construction, sentiment, and emotional dynamics with cohort-specific adaptation, a speaker tracking system (170) maintaining identity continuity across movements and audio variations, and an output generator (180) producing structured multi-speaker transcripts with semantic annotations, visualization dashboards showing spatial interaction patterns and knowledge transfer networks, and compliance documentation verifying consent adherence.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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