Computational Methods For Structured Sparse Component Analysis of Convolutive Speech Mixtures

• Presented at: The 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Kyoto, Japan, March 25-30, 2012
• Published in: Proceeding of the 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
• Publication date: 2012

We cast the under-determined convolutive speech separation as sparse approximation of the spatial spectra of the mixing sources. In this framework we compare and contrast the major practical algorithms for structured sparse recovery of speech signal. Specific attention is paid to characterization of the measurement matrix. We first propose how it can be identified using the Image model of multi-path effect where the acoustic parameters are estimated by localizing a speaker and its images in a free space model. We further study the circumstances in which the coherence of the projections induced by microphone array design tend to affect the recovery performance.

Keywords: Structured sparse signal recovery, Convolutive source separation, Image model, Sparse microphone array

Reference

• EPFL-CONF-174335

Record created on 2012-01-21, modified on 2012-05-09