DocumentCode :
1749385
Title :
Blind deconvolution of reverberated speech signals via regularization
Author :
Liu, Juan ; Malvar, Henrique
Author_Institution :
Beckman Inst., Univ. of Illinois, Urbana, IL, USA
Volume :
5
fYear :
2001
fDate :
2001
Firstpage :
3037
Abstract :
This paper explores blind deconvolution of reverberated speech signals in microphone array applications. Two regularization approaches are proposed based on available a priori knowledge. The regularized least-squares (LS) approach uses the speech signal characteristics and the lowpass nature of the reverberation channel; and the regularized cross correlation (CR) approach requires more precise knowledge of reverberation which can be obtained through training. The two methods are robust to the presence of noise
Keywords :
acoustic correlation; acoustic signal processing; array signal processing; deconvolution; least mean squares methods; microphones; reverberation; speech processing; blind deconvolution; cross correlation approach; least-squares approach; microphone array applications; regularization approaches; reverberated speech signals; reverberation channel; speech signal characteristics; speech. processing; Acoustic noise; Chromium; Convolution; Deconvolution; Linear predictive coding; Microphone arrays; Noise robustness; Reverberation; Speech analysis; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
ISSN :
1520-6149
Print_ISBN :
0-7803-7041-4
Type :
conf
DOI :
10.1109/ICASSP.2001.940298
Filename :
940298
Link To Document :
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