Cochannel Speech Separation Based on Clustering

Abstract

Abstract:

Abstract: This paper proposes an unsupervised clustering approach for cochannel speech separation to solve the problem that many auditory scene analysis (CASA) systems using training model to require the availability of pretrained speaker models and prior knowledge of participating speakers. The system produces simultaneous streams of mixture signal through multipitch tracking algorithm, and searches for the optimal assignment of simultaneous speech streams by maximizing the between and withincluster scatter matrix ratio to separate the mixtures. The system does not require trained speaker models, improves obviously the performance of cochannel separation, which offers a good solution to separate cochannel speech.

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Key words:

, Key words: , CASA； cochannel speech separation； clustering

CLC Number:

TP391

WU Chun， LIANG Zhengyou. Cochannel Speech Separation Based on Clustering[J]. Computer and Modernization, 2014, 0(4): 86-88.

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