Multi-party Speech Recovery Exploiting Structured Sparsity Models

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.


Published in:
Proceeding of Interspeech
Presented at:
12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 28-31, 2011
Year:
2011
Keywords:
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 Record created 2011-10-23, last modified 2018-03-18

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