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

doi:10.1109/ICASSP.2014.6853972

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

School of Indigenous Studies

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

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 language	English
Title of host publication	IEEE International Conference on Acoustics, Speech and Signal Processing
Place of Publication	Florence, Italy
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	2114-2118
Volume	NA
ISBN (Print)	9781479928927
DOIs	https://doi.org/10.1109/ICASSP.2014.6853972
Publication status	Published - 2014
Event	2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014 - Italy, Florence, Italy Duration: 4 May 2014 → 9 May 2014 Conference number: 106632

Conference

Conference	2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014
Abbreviated title	ICASSP 2014
Country/Territory	Italy
City	Florence
Period	4/05/14 → 9/05/14

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10.1109/ICASSP.2014.6853972

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Atcheson, M., Jafari, I., Togneri, R., & Nordholm, S. E. (2014). On the use of contextual time-frequency information for full-band clustering-based convolutive blind source separation. In IEEE International Conference on Acoustics, Speech and Signal Processing (Vol. NA, pp. 2114-2118). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICASSP.2014.6853972

@inproceedings{d8611ed88e3649268d306b36fc365f2c,

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

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. {\textcopyright} 2014 IEEE.",

author = "Matt Atcheson and I. Jafari and Roberto Togneri and S.E. Nordholm",

year = "2014",

doi = "10.1109/ICASSP.2014.6853972",

language = "English",

isbn = "9781479928927",

volume = "NA",

pages = "2114--2118",

booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",

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Atcheson, M, Jafari, I, Togneri, R & Nordholm, SE 2014, On the use of contextual time-frequency information for full-band clustering-based convolutive blind source separation. in IEEE International Conference on Acoustics, Speech and Signal Processing. vol. NA, IEEE, Institute of Electrical and Electronics Engineers, Florence, Italy, pp. 2114-2118, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, 4/05/14. https://doi.org/10.1109/ICASSP.2014.6853972

On the use of contextual time-frequency information for full-band clustering-based convolutive blind source separation. / Atcheson, Matt; Jafari, I.; Togneri, Roberto et al.
IEEE International Conference on Acoustics, Speech and Signal Processing. Vol. NA Florence, Italy: IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 2114-2118.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

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T1 - On the use of contextual time-frequency information for full-band clustering-based convolutive blind source separation

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AU - Jafari, I.

AU - Togneri, Roberto

AU - Nordholm, S.E.

N1 - Conference code: 106632

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

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DO - 10.1109/ICASSP.2014.6853972

M3 - Conference paper

SN - 9781479928927

VL - NA

SP - 2114

EP - 2118

BT - IEEE International Conference on Acoustics, Speech and Signal Processing

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Florence, Italy

T2 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014

Y2 - 4 May 2014 through 9 May 2014

ER -

Atcheson M, Jafari I, Togneri R, Nordholm SE. On the use of contextual time-frequency information for full-band clustering-based convolutive blind source separation. In IEEE International Conference on Acoustics, Speech and Signal Processing. Vol. NA. Florence, Italy: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 2114-2118 doi: 10.1109/ICASSP.2014.6853972

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

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