An approach for solving the permutation problem of convolutive blind source separation based on statistical signal models

Radoslaw Mazur*, Alfred Mertins

*Corresponding author for this work
25 Citations (Scopus)

Abstract

In this paper, we present a new algorithm for solving the permutation ambiguity in convolutive blind source separation. Transformed to the frequency domain, existing algorithms can efficiently solve the reduction of the source separation problem into independent instantaneous separation in each frequency bin. However this independency leads to the problem of correctly aligning these single bins. The new algorithm models the frequency-domain separated signals by means of the generalized Gaussian distribution and employs the small deviation of the parameters between neighboring bins for the detection of correct permutations. The performance of the algorithm will be demonstrated on synthetic and real-world data.

Original languageEnglish
Article number4740156
JournalIEEE Transactions on Audio, Speech and Language Processing
Volume17
Issue number1
Pages (from-to)117-126
Number of pages10
ISSN1558-7916
DOIs
Publication statusPublished - 01.01.2009

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