On the use of contextual time-frequency information for full-band clustering-based convolutive blind source separation

Matt Atcheson, I. Jafari, Roberto Togneri, S.E. Nordholm

Research output: Chapter in Book/Conference paperConference paper

5 Citations (Scopus)

Abstract

In this paper we propose to incorporate contextual time-frequency information for clustering-based blind source separation. Previous clustering-based approaches have successfully used clustering techniques to estimate time-frequency separation masks; however, these approaches generally do not consider the contextual information of each time-frequency slot. Motivated by the homogenous behavior of speech signals, we modify the fuzzy c-means clustering to bias the results in favor of cluster membership homogeneity within localized neighborhoods in the time-frequency space. Experimental evaluations in both simulated and real-world underdetermined environments demonstrate improvement in source separation performance over previous clustering approaches. © 2014 IEEE.
Original languageEnglish
Title of host publicationIEEE International Conference on Acoustics, Speech and Signal Processing
Place of PublicationFlorence, Italy
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages2114-2118
VolumeNA
ISBN (Print)9781479928927
DOIs
Publication statusPublished - 2014
Event2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014 - Italy, Florence, Italy
Duration: 4 May 20149 May 2014
Conference number: 106632

Conference

Conference2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014
Abbreviated titleICASSP 2014
CountryItaly
CityFlorence
Period4/05/149/05/14

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