Blind speech separation in convolutive mixtures using non-Gaussianity maximization and inverse filters

In this paper, we proposed the approach which combines inverse filter criteria with non-Gaussianity to separate convolutive mixtures of speech in the time domain. In this case, the proposed method first extract innovation processes of speech sources by non-Gaussianity maximization and then artificially color them by re-coloration filters. Computer simulation experiments are presented to illustrate the proposed approach.