Independent Vector Analysis Based MIMO Deconvolution: Exploiting Spatial Diversity Through Back Projection

This paper deals with the scaling ambiguity issue in blind convolutive source separation when performed in the frequency domain. It considers two major techniques, mainly the Minimal Distortion Principle and the Back Projection, that allow to overcome the aforementioned indeterminacy. The main contr...

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Bibliographic Details
Main Authors: Belouchrani, Adel, Mendjel, Nacira, Berrah, Lynda, Tebache, Soufiane
Format: Conference Proceeding
Language:English
Subjects:
Back projection
Deconvolution
Estimation
Frequency-domain analysis
Independent Vector Analysis
Minimal Distortion Principle
Signal processing algorithms
SIMO Deconvolution
Source separation
Spatial diversity
Speech enhancement
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Summary:This paper deals with the scaling ambiguity issue in blind convolutive source separation when performed in the frequency domain. It considers two major techniques, mainly the Minimal Distortion Principle and the Back Projection, that allow to overcome the aforementioned indeterminacy. The main contribution of this paper consists of exploiting one of the most beneficial outcomes of the Back Projection, which is spatial diversity. Our proposed approach applies Single Input Multiple Output deconvolution to the outputs of the back projected source signals, after their estimation by the Independent Vector Analysis algorithm. This method has the advantage of both improving the estimation accuracy and removing the channel effect. Experimental results show the effectiveness of our proposal, compared to the traditional used Minimum Distortion Principle.
ISSN:2693-3551
DOI:10.1109/SSP53291.2023.10207982