Convolutive Blind Speech Separation by Decorrelation

被引：0

作者：

Wang, Fuxiang ^{[1
]}

Zhang, Jun ^{[1
]}

机构：

[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100083, Peoples R China

来源：

ADVANCES IN NEURO-INFORMATION PROCESSING, PT I | 2009年 / 5506卷

关键词：

NONSTATIONARY SOURCES; DIAGONALIZATION; MIXTURES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a new method for convolutive blind speech separation by decorrelation. First, by the design of a FIR separating filter and a whitening process of the observed data, the separation of convolutive speech mixtures are transformed to find a semi-unitary separating matrix. Then we estimate the separating semi-unitary matrix by the semi-unitary joint diagonalization for a set of correlation matrices. And a numerical algorithm for semi-unitary joint diagonalization is proposed. Simulation results of speech separation demonstrate the effectiveness of the new approach.

引用

页码：737 / 744

页数：8

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