A blind source separation of instantaneous acoustic mixtures using natural gradient method

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

Proceedings - 2012 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2012

First Page

124

Last Page

129

Publication Date

1-1-2012

Abstract

A variety of applications concerning communication signal processing involves recovering unobserved signals or 'sources' from several observed mixtures, and 'cocktail party effect' is a good paradigm related to this process. Given a set of linearly superimposed acoustic signals without knowledge about the sources makes Blind Source Separation (BSS) a very suitable scheme. A more popular approach of BSS, Independent Component Analysis, has been exploited which basically senses the statistical independence of the source signal estimates to achieve separation. A set of interfering signals present in a typical acoustic environment has been instantaneously combined with a pre-determined mixing matrix. A great weight has been given on an excellent rendition of the Infomax technique of Independent Component Analysis (ICA), called the Natural Gradient Method, to employ a cost function that would yield an optimized de-mixing matrix, producing fairly estimated source signals. By varying the learning rate and the score function, a robust performance of the Natural Gradient has been exhibited, maximizing the separation quality, stability and convergence speed. © 2012 IEEE.

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Digitial Object Identifier (DOI)

10.1109/ICCSCE.2012.6487128

Disciplines

Electrical and Computer Engineering

Keywords

Blind source separation; Independent component analysis; Auditory selective attention

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