Multi-party Speech Recovery Exploiting Structured Sparsity Models

• Presented at: 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 28-31
• Published in: Proceeding of the 12th Annual Conference of the International Speech Communication Association (ISCA), INTERSPEECH 2011
• Publication date: 2011

We study the sparsity of spectro-temporal representation of speech in reverberant acoustic conditions. This study motivates the use of structured sparsity models for efficient speech recovery. We formulate the underdetermined convolutive speech separation in spectro-temporal domain as the sparse signal recovery where we leverage model-based recovery algorithms. To tackle the ambiguity of the real acoustics, we exploit the Image model of the enclosures to estimate the room impulse response function through a structured sparsity constraint optimization. The experiments conducted on real data recordings demonstrate the effectiveness of the proposed approach for multi-party speech applications.

Keywords: speech sparsity, structured sparsity models, underdetermined convolutive speech separation, Image model

Reference

• EPFL-CONF-169695

Record created on 2011-10-23, modified on 2012-05-09