A Quantitative Evaluation of a Bio-inspired Sound Segregation Technique for Two- and Three-Source Mixtures

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. 1 The sound source separation problem In our life we are confronted to situation in which a mixture of sound sources is present in the environment and our goal is to extract one of the sources among others. While the auditory system may not always succeed in this goal, the range of situations in which recognition is possible in the presence of competing sources highlights the flexibility and robustness of human in speech perception. Here we propose a technique that roughly simulates the behavior of the auditory pathway. Our separation technique uses the Computational Auditory Scene Analysis [1]. 2 The proposed model An enhanced FIR Gammatone filterbank is used to mimic the behavior of the cochlea [2]. From the output of t...

• Type: Conference
• Year: 2004
• Where: NN
• Authors: Ramin Pichevar, Jean Rouat
• Keywords: NN 2004, Separation Technique, Sound Source Separation, Source Separation Technique