An Approach to Solving a Permutation Problem of Frequency Domain Independent Component Analysis for Blind Source Separation of Speech Signals
نویسندگان
چکیده
Independent component analysis (ICA) in the frequency domain is used for solving the problem of blind source separation (BSS). However, this method has some problems. For example, a general ICA algorithm cannot determine the permutation of signals which is important in the frequency domain ICA. In this paper, we propose an approach to the solution for a permutation problem. The idea is to effectively combine two conventional approaches. This approach improves the signal separation performance by exploiting features of the conventional approaches. We show the simulation results using artificial data. Keywords—Blind source separation, Independent component analysis, Frequency domain, Permutation ambiguity.
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Using information theoretic distance measures for solving the permutation problem of blind source separation of speech signals
The problem of blind source separation (BSS) of convolved acoustic signals is of great interest for many classes of applications. Due to the convolutive mixing process, the source separation is performed in the frequency domain, using independent component analysis (ICA). However, frequency domain BSS involves several major problems that must be solved. One of these is the permutation problem. ...
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