Blind audio source separation using weight initialized independent component analysis

Blind audio source separation is a promising area for various applications like humanoids, human machine inter- action or adverse control mechanism, etc. ICA is a predominant approach for source separation in blind scenario. There are various versions of ICA to solve this purpose like Fast ICA, JADE...

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Bibliographic Details
Published in2015 1st International Conference on Next Generation Computing Technologies (NGCT) pp. 563 - 566
Main Authors Yadav, Ritesh Kumar, Mehra, Rajesh, Dubey, Naveen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2015
Subjects
Blind source separation
Computers
Convergence
Entropy
Independent component analysis
kurtosis
negentropy
Next generation networking
Signal processing algorithms
Source separation
whitening
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Summary:Blind audio source separation is a promising area for various applications like humanoids, human machine inter- action or adverse control mechanism, etc. ICA is a predominant approach for source separation in blind scenario. There are various versions of ICA to solve this purpose like Fast ICA, JADE, and C-ICA. The convergence speed and quality of separation is an issue. In this work a weight initialization approach is proposed for optimizing the convergence speed and experimental results reflects up to 28.57% that the proposed weight initialized ICA gives better convergence speed in comparison of Fast ICA. Here a critically determined ideal mixing system is considered where no noise component is taken into account.
DOI:10.1109/NGCT.2015.7375183