A quantitative evaluation of a bio-inspired sound segregation technique for two- and three-source mixtures

Authors:
Ramin Pichevar;Jean Rouat
Affiliations:
Dept. of Elect. Eng, University of Sherbrooke, QC, Canada;Dept. of Elect. Eng, University of Sherbrooke, QC, Canada
Venue:
Nonlinear Speech Modeling and Applications
Year:
2005

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Abstract

A sound source separation technique based on a bio-inspired neural network, capable of functioning in more than two-source mixtures, is proposed. Separation results are compared with other proposed techniques in the literature using quantitative evaluation criteria.