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ICASSP
2009
IEEE

Using the scaling ambiguity for filter shortening in convolutive blind source separation

10 years 4 months ago
Using the scaling ambiguity for filter shortening in convolutive blind source separation
In this paper, we propose to use the scaling ambiguity of convolutive blind source separation for shortening the unmixing filters. An often used approach for separating convolutive mixtures is the transformation to the time-frequency domain where an instantaneous ICA algorithm can be applied for each frequency separately. This approach leads to the so called permutation and scaling ambiguity. While different methods for the permutation problem have been widely studied, the solution for the scaling problem is usually based on the minimal distortion principle. We propose an alternative approach that allows the unmixing filters to be as short as possible. Shorter unmixing filters will suffer less from circular-convolution effects that are inherent to unmixing approaches based on binwise ICA followed by permutation and scaling correction. The results for the new algorithm will be shown on a realworld example.
Radoslaw Mazur, Alfred Mertins
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Radoslaw Mazur, Alfred Mertins
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