DocumentCode :
3347739
Title :
Blind source separation of nonstationary convolutively mixed signals in the subband domain
Author :
Russell, Iain ; Xi, Jiangtao ; Mertins, Alfred ; Chicharo, Joe
Author_Institution :
Sch. of Elec., Comp., & Tele. Eng., Wollongong Univ., NSW, Australia
Volume :
5
fYear :
2004
fDate :
17-21 May 2004
Abstract :
The paper proposes a new technique for blind source separation (BSS) in the subband domain using an extended lapped transform (ELT) decomposition for nonstationary, convolutively mixed signals. As identified by S. Araki et al. (see Proc. 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation - ICA2003, p.499-504, 2003), the motivation for subband-based BSS is the drawback of frequency domain BSS when dealing with separating mixed speech signals over a few seconds resulting in few samples in individual frequency bins leading to poor separation performance. In the proposed approach, mixed signals are decomposed into subband components by an ELT and within each subband a time domain Newton BSS algorithm is employed based on the nonstationarity property of the input signals and the joint diagonalization of output correlation matrices with time varying second order statistics (SOS). This subband version is compared to a fullband version using the same BSS algorithm.
Keywords :
FIR filters; Newton method; blind source separation; channel bank filters; convolution; matrix algebra; speech processing; transforms; BSS; FIR filterbank; blind source separation; correlation matrices; extended lapped transform decomposition; mixed speech signals; nonstationary convolutively mixed signals; subband domain; time domain Newton algorithm; time varying second order statistics; Blind source separation; Discrete Fourier transforms; Finite impulse response filter; Fourier transforms; Frequency domain analysis; Frequency estimation; Signal processing; Signal processing algorithms; Source separation; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8484-9
Type :
conf
DOI :
10.1109/ICASSP.2004.1327152
Filename :
1327152
Link To Document :
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