Blind Separation of Underdetermined Convolutive Mixtures Using Their Time-Frequency Representation

This paper considers the blind separation of nonstationary sources in the underdetermined convolutive mixture case. We introduce, two methods based on the sparsity assumption of the sources in the time-frequency (TF) domain. The first one assumes that the sources are disjoint in the TF domain, i.e.,...

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Bibliographic Details
Published in:IEEE transactions on audio, speech, and language processing speech, and language processing, 2007-07, Vol.15 (5), p.1540-1550
Main Authors: Aissa-El-Bey, A., Abed-Meraim, K., Grenier, Y.
Format: Article
Language:English
Subjects:
Biomedical signal processing
Blind source separation
Blind source separation (BSS)
Blinds
Channels
convolutive mixture
Data communication
Deconvolution
Delay
Engineering Sciences
Frequency distribution
Mathematical models
Natural language processing
Projection
Representations
Separation
Signal and Image processing
Signal processing algorithms
Signal resolution
Source separation
sparse signal decomposition/representation
Speech
Speech processing
speech signals
Studies
subspace projection
time-frequency distribution (TFD)
underdetermined/overcomplete representation
vector clustering
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Summary:This paper considers the blind separation of nonstationary sources in the underdetermined convolutive mixture case. We introduce, two methods based on the sparsity assumption of the sources in the time-frequency (TF) domain. The first one assumes that the sources are disjoint in the TF domain, i.e., there is at most one source signal present at a given point in the TF domain. In the second method, we relax this assumption by allowing the sources to be TF-nondisjoint to a certain extent. In particular, the number of sources present (active) at a TF point should be strictly less than the number of sensors. In that case, the separation can be achieved thanks to subspace projection which allows us to identify the active sources and to estimate their corresponding time-frequency distribution (TFD) values. Another contribution of this paper is a new estimation procedure for the mixing channel in the underdetermined case. Finally, numerical performance evaluations and comparisons of the proposed methods are provided highlighting their effectiveness.
ISSN:1558-7916
2329-9290
1558-7924
2329-9304
DOI:10.1109/TASL.2007.898455