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ICASSP
2009
IEEE

Blind system identification for speech dereverberation with Forced Spectral Diversity

10 years 4 months ago
Blind system identification for speech dereverberation with Forced Spectral Diversity
The common zeros problem for blind system identification (BSI) is well known. It degrades the performance of classic BSI algorithms and therefore imposes the limit on the performance of subsequent speech dereverberation. The effect of near-common zeros has recently been studied in terms of channel diversity and the degradation in performance of BSI and multichannel equalization algorithms has been shown. We now introduce a novel approach to improve channel diversity which we refer to as Forced Spectral Diversity (FSD). The FSD concept uses a combination of spectral shaping filters and effective channel undermodelling. Simulation results show that the proposed approach achieves improved performance with reduced complexity for multichannel BSI in a room acoustics example.
Xiang Lin, Andy W. H. Khong, Patrick A. Naylor
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Xiang Lin, Andy W. H. Khong, Patrick A. Naylor
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