DocumentCode :
111787
Title :
Multichannel Sound Source Dereverberation and Separation for Arbitrary Number of Sources Based on Bayesian Nonparametrics
Author :
Otsuka, Takayuki ; Ishiguro, Katsuhiko ; Yoshioka, Takashi ; Sawada, Hideyuki ; Okuno, Hiroshi G.
Author_Institution :
NTT Commun. Sci. Labs., NTT Corp., Kyoto, Japan
Volume :
22
Issue :
12
fYear :
2014
fDate :
Dec. 2014
Firstpage :
2218
Lastpage :
2232
Abstract :
Multichannel signal processing using a microphone array provides fundamental functions for coping with multi-source situations, such as sound source localization and separation, that are needed to extract the auditory information for each source. Auditory uncertainties about the degree of reverberation and the number of sources are known to degrade performance or limit the practical application of microphone array processing. Such uncertainties must therefore be overcome to realize general and robust microphone array processing. These uncertainty issues have been partly addressed-existing methods focus on either source number uncertainty or the reverberation issue, where joint separation and dereverberation has been achieved only for the overdetermined conditions. This paper presents an all-round method that achieves source separation and dereverberation for an arbitrary number of sources including underdetermined conditions. Our method uses Bayesian nonparametrics that realize an infinitely extensible modeling flexibility so as to bypass the model selection in the separation and dereverberation problem, which is caused by the source number uncertainty. Evaluation using a dereverberation and separation task with various numbers of sources including underdetermined conditions demonstrates that (1) our method is applicable to the separation and dereverberation of underdetermined mixtures, and that (2) the source extraction performance is comparable to that of a state-of-the-art method suitable only for overdetermined conditions.
Keywords :
Bayes methods; array signal processing; audio signal processing; blind source separation; microphone arrays; nonparametric statistics; reverberation; Bayesian nonparametrics; auditory uncertainties; blind source separation; joint separation-dereverberation problem; microphone array processing; multichannel signal processing; multichannel sound source dereverberation; multichannel sound source separation; sound source localization; source extraction performance; source number uncertainty; Arrays; Bayes methods; Microphones; Reverberation; Source separation; Uncertainty; Vectors; Bayesian nonparametrics; Markov chain Monte Carlo method; blind dereverberation; blind source separation; microphone array processing; underdetermined mixtures;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
2329-9290
Type :
jour
DOI :
10.1109/TASLP.2014.2363790
Filename :
6926796
Link To Document :
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