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 [BibTeX] [Marc21]
Model-Based Compressive Sensing for Multi-Party Distant Speech Recognition
Type of publication: Idiap-RR
Citation: Asaei_Idiap-RR-04-2011
Number: Idiap-RR-04-2011
Year: 2011
Month: 3
Institution: Idiap
Abstract: 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.
Keywords: Model-Based Compressive Sensing, Multi-party Speech Recognition, Overlapping Speech, Sparse Component Analysis, Sparse Signal Recovery
Projects Idiap
Authors Asaei, Afsaneh
Bourlard, Hervé
Cevher, Volkan
Crossref by Asaei_ICASSP_2011
Added by: [ADM]
Total mark: 0
  • Asaei_Idiap-RR-04-2011.pdf