Year: 2010
Journal of Computational Mathematics, Vol. 28 (2010), Iss. 3 : pp. 371–385
Abstract
We study a time domain decorrelation method of source signal separation from convolutive sound mixtures based on an infinite impulse response (IIR) model. The IIR model uses fewer parameters to capture the physical mixing process and is useful for finding low dimensional separating solutions. We present inversion formulas to decorrelate the mixture signals and derive filter equations involving second order time lagged statistics of mixtures. We then formulate an $l_1$ constrained minimization problem and solve it by an iterative method. Numerical experiments on recorded sound mixtures show that our method is capable of sound separation in low dimensional parameter spaces with good perceptual quality and low correlation coefficient comparable to the known infomax method.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/jcm.2009.10-m2900
Journal of Computational Mathematics, Vol. 28 (2010), Iss. 3 : pp. 371–385
Published online: 2010-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 15
Keywords: Blind Decorrelation Convolutive Mixtures IIR Modeling $l_1$ Constrained Minimization.