REPORT Asaei_Idiap-RR-04-2011/IDIAP Model-Based Compressive Sensing for Multi-Party Distant Speech Recognition Asaei, Afsaneh Bourlard, Hervé Cevher, Volkan Model-Based Compressive Sensing Multi-party Speech Recognition Overlapping Speech Sparse Component Analysis Sparse Signal Recovery EXTERNAL PUBLIC Idiap-RR-04-2011 2011 Idiap March 2011 We leverage the recent algorithmic advances in compressive sensing, and propose a novel source separation algorithm for efficient recovery of convolutive speech mixtures in spectro-temporal domain. Compared to the common sparse component analysis techniques, our approach fully exploits structured sparsity models to obtain substantial improvement over the existing state-of-the-art. We evaluate our method for separation and recognition of a target speaker in a multi-party scenario. Our results provide compelling evidence of the effectiveness of sparse recovery formulations in speech recognition.