Model based Binaural Enhancement of Voiced and Unvoiced Speech

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

5 Citationer (Scopus)
235 Downloads (Pure)

Resumé

This paper deals with the enhancement of speech in presence
of non-stationary babble noise. A binaural speech enhancement framework is proposed which takes into account both
the voiced and unvoiced speech production model. The usage
of this model in enhancement requires the Short term predictor (STP) parameters and the pitch information to be estimated. This paper uses a codebook based approach for estimating the STP parameters and a parametric binaural method
is proposed for estimating the pitch parameters. Improvements in objective score are shown when using the voicedunvoiced speech model in comparison to the conventional unvoiced speech model
OriginalsprogEngelsk
TitelIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
ForlagIEEE
Publikationsdato2017
Sider666-670
ISBN (Elektronisk)978-1-5090-4117-6
DOI
StatusUdgivet - 2017
BegivenhedThe 42nd IEEE International Conference on Acoustics, Speech and Signal Processing: The Internet of Signals - New Orleans, USA
Varighed: 5 mar. 20179 mar. 2017
http://www.ieee-icassp2017.org/
http://www.ieee-icassp2017.org/

Konference

KonferenceThe 42nd IEEE International Conference on Acoustics, Speech and Signal Processing
LandUSA
ByNew Orleans
Periode05/03/201709/03/2017
Internetadresse
NavnI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149

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Speech enhancement

Citer dette

Kavalekalam, M. S., Christensen, M. G., & Boldt, J. B. (2017). Model based Binaural Enhancement of Voiced and Unvoiced Speech. I IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 (s. 666-670). IEEE. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings https://doi.org/10.1109/ICASSP.2017.7952239
Kavalekalam, Mathew Shaji ; Christensen, Mads Græsbøll ; Boldt, Jesper B. / Model based Binaural Enhancement of Voiced and Unvoiced Speech. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE, 2017. s. 666-670 (I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings).
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abstract = "This paper deals with the enhancement of speech in presenceof non-stationary babble noise. A binaural speech enhancement framework is proposed which takes into account boththe voiced and unvoiced speech production model. The usageof this model in enhancement requires the Short term predictor (STP) parameters and the pitch information to be estimated. This paper uses a codebook based approach for estimating the STP parameters and a parametric binaural methodis proposed for estimating the pitch parameters. Improvements in objective score are shown when using the voicedunvoiced speech model in comparison to the conventional unvoiced speech model",
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Kavalekalam, MS, Christensen, MG & Boldt, JB 2017, Model based Binaural Enhancement of Voiced and Unvoiced Speech. i IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE, I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, s. 666-670, New Orleans, USA, 05/03/2017. https://doi.org/10.1109/ICASSP.2017.7952239

Model based Binaural Enhancement of Voiced and Unvoiced Speech. / Kavalekalam, Mathew Shaji; Christensen, Mads Græsbøll; Boldt, Jesper B.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE, 2017. s. 666-670 (I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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Kavalekalam MS, Christensen MG, Boldt JB. Model based Binaural Enhancement of Voiced and Unvoiced Speech. I IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017. IEEE. 2017. s. 666-670. (I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings). https://doi.org/10.1109/ICASSP.2017.7952239