Multi-party speech recovery exploiting structured sparsity models
Afsaneh Asaei, Mohammad Javad Taghizadeh, Hervé A. Bourlard, Volkan Cevher · 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 recov-ery. We formulate the underdetermined convolutive speech sep-aration 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 func-tion 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. Index Terms: speech sparsity, structured sparsity models, un-derdetermined convolutive speech separation, Image Model