Kalman filter for speech enhancement in cocktail party scenarios using a codebook-based approach

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Abstract

Enhancement of speech in non-stationary background noise is a challenging task, and conventional single channel speech enhancement algorithms have not been able to improve the speech intelligibility in such scenarios. The work proposed in this paper investigates a single channel Kalman filter based speech enhancement algorithm, whose parameters are estimated using a codebook based approach. The results indicate that the enhancement algorithm is able to improve the speech intelligibility and quality according to objective measures. Moreover, we investigate the effects of utilizing a speaker specific trained codebook over a generic speech codebook in relation to the performance of the speech enhancement system.
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Enhancement of speech in non-stationary background noise is a challenging task, and conventional single channel speech enhancement algorithms have not been able to improve the speech intelligibility in such scenarios. The work proposed in this paper investigates a single channel Kalman filter based speech enhancement algorithm, whose parameters are estimated using a codebook based approach. The results indicate that the enhancement algorithm is able to improve the speech intelligibility and quality according to objective measures. Moreover, we investigate the effects of utilizing a speaker specific trained codebook over a generic speech codebook in relation to the performance of the speech enhancement system.
Original languageEnglish
JournalI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149
DOI
StatePublished - Apr 2016
Publication categoryResearch
Peer-reviewedYes
EventThe 41st IEEE International Conference on Acoustics, Speech and Signal Processing - Shanghai, China
Duration: 20 Mar 201625 Mar 2016
http://www.icassp2016.org/

Conference

ConferenceThe 41st IEEE International Conference on Acoustics, Speech and Signal Processing
CountryChina
CityShanghai
Period20/03/201625/03/2016
Internet address
ID: 245548231