Speech Separation Using MATLAB - Computational Auditory Scene Analysis Approach
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Resource Overview
Speech separation algorithm based on Computational Auditory Scene Analysis (CASA), which attempts to simulate human auditory psychological and physiological processes through computer technology, enabling computers to process sounds (separate and interpret) similarly to human ears. This emerging interdisciplinary research topic involves signal processing techniques including gammatone filtering, pitch tracking, and binary masking implementation.
Detailed Documentation
Speech separation algorithms based on Computational Auditory Scene Analysis represent an emerging interdisciplinary research field. These algorithms simulate human auditory psychological processes and physiological mechanisms, aiming to equip computers with human-like sound processing capabilities - specifically the ability to separate and interpret auditory signals. The technical implementation typically involves MATLAB signal processing workflows including: gammatone filterbank analysis for cochlear modeling, autocorrelation-based pitch detection algorithms, and time-frequency masking techniques for source separation. This technology leverages advanced computational methods and demonstrates significant potential for applications in hearing aids, speech recognition systems, and audio forensics.
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