NDLI: Adaptive decorrelation filtering algorithm for speech source separation in uncorrelated noises

Content Provider	IEEE Xplore Digital Library
Author	Rong Hu Yunxin Zhao
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Sci., Missouri Univ., Columbia, MO, USA (Rong Hu; Yunxin Zhao)
Abstract	A time-domain vector formulation is presented on analysis and solution of the adaptive decorrelation filtering (ADF) system for blind speech source separation in additive background noise. The formulation leads to a derivation of a gradient descent algorithm and offers insights into the impact of uncorrelated white noise on ADF systems. A new noise-adapted ADF algorithm is then derived by modifying the decorrelation criterion function to exclude noise impact on cross-correlation information of ADF outputs. Speech separation simulations were based on convolutive mixtures of TIMIT speech data generated with long impulse response measured in a real reverberant acoustic experiment. The proposed algorithm significantly improved convergence rate, gains in target-to-interference ratio at ADF outputs, and phone accuracy of separated target speech source.
Sponsorship	IEEE Signal Processing Soc
File Size	249796
File Format	PDF
ISBN	0780388747
ISSN	15206149
DOI	10.1109/ICASSP.2005.1415313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decorrelation Filtering algorithms Source separation Finite impulse response filter Acoustic noise Background noise Time domain analysis Speech analysis Adaptive filters Speech recognition
Content Type	Text
Resource Type	Article

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