Multichannel transient acoustic signal classification using task-driven dictionary with joint sparsity and beamforming

Yang Zhang, Nasser M. Nasrabadi, Mark Allan Hasegawa-Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We are interested in a multichannel transient acoustic signal classification task which suffers from additive/convolutionary noise corruption. To address this problem, we propose a double-scheme classifier that takes the advantage of multichannel data to improve noise robustness. Both schemes adopt task-driven dictionary learning as the basic framework, and exploit multichannel data at different levels - scheme 1 imposes joint sparsity constraint while learning the dictionary and classifier; scheme 2 adopts beamforming at signal formation level. In addition, matched filter and robust ceptral coefficients are applied to improve noise robustness of the input feature. Experiments show that the proposed classifier significantly outperforms the baseline algorithms.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1866-1870
Number of pages5
ISBN (Electronic)9781467369978
DOIs
StatePublished - Aug 4 2015
Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
Duration: Apr 19 2014Apr 24 2014

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2015-August
ISSN (Print)1520-6149

Other

Other40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
CountryAustralia
CityBrisbane
Period4/19/144/24/14

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Keywords

  • Transient acoustic signal
  • beamforming
  • joint sparsity
  • multichannel
  • task-driven dictionary learning

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Zhang, Y., Nasrabadi, N. M., & Hasegawa-Johnson, M. A. (2015). Multichannel transient acoustic signal classification using task-driven dictionary with joint sparsity and beamforming. In 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings (pp. 1866-1870). [7178294] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2015-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2015.7178294