A Single Input Model for Sequential Processing of Speech Separation

Speech separation based on auditory scene analysis (ASA) has been widely studied. A computational ASA (CASA) model, in which a mixed signal is sequentially decomposed into frequency signals, has been also proposed. Four feature types of ASA are extracted from the decomposed frequency signals, and the decomposed frequency signals are regrouped by examining the characteristics of the extracted features. Finally separated speeches are obtained. In this study, the CASA model is improved and pieced out, and the separation performance is examined via a computer simulation