A Fast and Efficient Frequency-Domain Method for Convolutive Blind Source Separation

Peng Xie
Steven L. Grant, Missouri University of Science and Technology

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1354

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In this paper, the problem of blind separation of a convolutive mixture of audio signals is considered. A fast and efficient frequency-domain blind source separation (BSS) method using Independent component analysis (ICA) is investigated. The main difficulties of this approach lie in the so called permutation and amplitude problems. In order to solve the permutation ambiguity, the final value of the ICA derived separation matrix of one frequency bin, is used to initialize the ICA iterations in the next frequency bin. The amplitude problem is addressed by utilizing the elements in the inverse of the separation matrix. Experimental results demonstrate that successful separation is achieved and compared with conventional frequency-domain BSS methods, it is less computationally complex and has faster convergence.