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
收藏
页码：737 / 744
页数：8
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