PERMUTATION CORRECTION AND SPEECH EXTRACTION BASED ON SPLIT SPECTRUM THROUGH FASTICA

Abstract

A blind source deconvolution method without indeterminacy of permutation and scaling is proposed by using notable features of split spectrum and locational information on signal sources. A method for extracting human speech exclusively is also proposed by taking advantage of the rule, the property of FastICA separates sources in order of large non-Gaussianity from their mixtures and the fact that human speeches are usually larger in non-Gaussianity than noises. The proposed methods have been verified by several experiments in a real room. 1