Phase-optimized K-SVD for signal extraction from underdetermined multichannel sparse mixtures

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Deleforge A, Kellermann W
Publisher: Institute of Electrical and Electronics Engineers Inc.
Publication year: 2015
Pages range: 355-359
ISBN: 9781467369978


Abstract


We propose a novel sparse representation for heavily underdetermined multichannel sound mixtures, i.e., with much more sources than microphones. The proposed approach operates in the complex Fourier domain, thus preserving spatial characteristics carried by phase differences. We derive a generalization of K-SVD which jointly estimates a dictionary capturing both spectral and spatial features, a sparse activation matrix, and all instantaneous source phases from a set of signal examples. This dictionary can be used to extract the learned signal from a new input mixture. The method is applied to the challenging problem of ego-noise reduction for robot audition. We demonstrate its superiority relative to conventional dictionary-based techniques using real-room recordings.



FAU Authors / FAU Editors

Deleforge, Antoine
Professur für Nachrichtentechnik
Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik


How to cite

APA:
Deleforge, A., & Kellermann, W. (2015). Phase-optimized K-SVD for signal extraction from underdetermined multichannel sparse mixtures. (pp. 355-359). Institute of Electrical and Electronics Engineers Inc..

MLA:
Deleforge, Antoine, and Walter Kellermann. "Phase-optimized K-SVD for signal extraction from underdetermined multichannel sparse mixtures." Proceedings of the 40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 Institute of Electrical and Electronics Engineers Inc., 2015. 355-359.

BibTeX: 

Last updated on 2018-19-04 at 03:35