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Primitive Auditory Segregation Based on Oscillatory Correlation
Author(s) -
Wang DeLiang
Publication year - 1996
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog2003_3
Subject(s) - auditory scene analysis , synchronization (alternating current) , computer science , set (abstract data type) , perception , auditory system , perspective (graphical) , dependency (uml) , auditory cortex , auditory perception , speech recognition , psychology , artificial intelligence , cognitive psychology , neuroscience , computer network , channel (broadcasting) , programming language
Auditory scene analysis is critical for complex auditory processing. We study auditory segregation from the neural network perspective, and develop a framework for primitive auditory scene analysis. The architecture is a laterally coupled two‐dimensional network of relaxation oscillators with a global inhibitor. One dimension represents time and another one represents frequency. We show that this architecture, plus systematic delay lines, can in real time group auditory features into a stream by phase synchrony and segregate different streams by desynchronization. The network demonstrates a set of psychological phenomena regarding primitive auditory scene analysis, including dependency on frequency proximity and the rate of presentation, sequential capturing, and competition among different perceptual organizations. We offer a neurocomputational theory—shifting synchronization theory—for explaining how auditory segregation might be achieved in the brain, and the psychological phenomenon of stream segregation. Possible extensions of the model are discussed.