An Oscillatory Correlation Frame work for Computational Auditory Scene Analysis

Part of Advances in Neural Information Processing Systems 12 (NIPS 1999)

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Authors

Guy J. Brown, DeLiang L. Wang

Abstract

A neural model is described which uses oscillatory correlation to segregate speech from interfering sound sources. The core of the model is a two-layer neural oscillator network. A sound stream is represented by a synchronized population of oscillators, and different streams are represented by desynchronized oscillator populations. The model has been evaluated using a corpus of speech mixed with interfering sounds, and produces an improvement in signal-to-noise ratio for every mixture.