Divergence for Blind Audio Source Separation

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-28 Number-1
Year of Publication : 2015
Authors : Deepak Rasaily, Rajesh Mehra, Naveen Dubey
  10.14445/22312803/IJCTT-V28P101

MLA

Deepak Rasaily, Rajesh Mehra, Naveen Dubey "Divergence for Blind Audio Source Separation". International Journal of Computer Trends and Technology (IJCTT) V28(1):1-4, October 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Blind Audio Source Separation is a technique to separate out audio signal from various sources recorded by number of microphones placed at different positions. ICA is dominant technique to separate independent components of signals from mixture. Inequality based divergence measure is used to develop a contrast function for source separation using ICA.This work addresses various divergence measures and performance of inequality based divergence measure. Experimental result reflects that Jenson Inequality based convex divergence measure gives better performance than other divergence measures such as Euclidian, Kullback leibler, Cauchy-Schwartz etc. Convex divergence measure for α= -1 gives 20-25% better and faster convergence than other and can be adopted for audio source separation by incorporating Independent component analysis.

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Keywords
Independent component analysis, Convex Divergence, Blind audio source separation, Inequality based divergence.