Model based Estimation of STP parameters for Binaural Speech Enhancement

Mathew Shaji Kavalekalam; Jesper Kjær Nielsen; Mads Græsbøll Christensen; Jesper Bünsow Boldt

doi:10.23919/EUSIPCO.2018.8553145

Model based Estimation of STP parameters for Binaural Speech Enhancement

Mathew Shaji Kavalekalam, Jesper Kjær Nielsen, Mads Græsbøll Christensen, Jesper Bünsow Boldt

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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Abstract

This paper deals with the estimation of the short-term predictor (STP) parameters of speech and noise in a binaural framework. A binaural model based approach is proposed for estimating the power spectral density (PSD) of speech and noise at the individual ears for an arbitrary position of the speech source. The estimated PSDs can be subsequently used for enhancement in a binaural framework. The experimental results show that taking into account the position of the speech source using the proposed method leads to improved modelling and enhancement of the noisy speech.

Original language	English
Title of host publication	2018 26th European Signal Processing Conference (EUSIPCO)
Publisher	IEEE
Publication date	2018
Article number	8553145
ISBN (Print)	978-90-827970-0-8, 978-1-5386-3736-4
ISBN (Electronic)	978-9-0827-9701-5
DOIs	https://doi.org/10.23919/EUSIPCO.2018.8553145
Publication status	Published - 2018
Event	26th European Signal Processing Conference (EUSIPCO 2018) - Rome, Italy Duration: 3 Sept 2018 → 7 Sept 2018 Conference number: 26 http://www.eusipco2018.org

Conference

Conference	26th European Signal Processing Conference (EUSIPCO 2018)
Number	26
Country/Territory	Italy
City	Rome
Period	03/09/2018 → 07/09/2018
Internet address	http://www.eusipco2018.org

Series	Proceedings of the European Signal Processing Conference
ISSN	2076-1465

Keywords

autoregressive modelling, binaural speech enhancement

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10.23919/EUSIPCO.2018.8553145

eusipco_2018_paper_1Accepted author manuscript, 350 KB

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@inproceedings{e43aeb1733be403998d57161da200543,

title = "Model based Estimation of STP parameters for Binaural Speech Enhancement",

abstract = "This paper deals with the estimation of the short-term predictor (STP) parameters of speech and noise in a binaural framework. A binaural model based approach is proposed for estimating the power spectral density (PSD) of speech and noise at the individual ears for an arbitrary position of the speech source. The estimated PSDs can be subsequently used for enhancement in a binaural framework. The experimental results show that taking into account the position of the speech source using the proposed method leads to improved modelling and enhancement of the noisy speech.",

keywords = "autoregressive modelling, binaural speech enhancement",

author = "Kavalekalam, {Mathew Shaji} and Nielsen, {Jesper Kj{\ae}r} and Christensen, {Mads Gr{\ae}sb{\o}ll} and Boldt, {Jesper B{\"u}nsow}",

year = "2018",

doi = "10.23919/EUSIPCO.2018.8553145",

language = "English",

isbn = "978-90-827970-0-8",

series = "Proceedings of the European Signal Processing Conference",

publisher = "IEEE",

booktitle = "2018 26th European Signal Processing Conference (EUSIPCO)",

address = "United States",

note = "26th European Signal Processing Conference (EUSIPCO 2018), EUSIPCO ; Conference date: 03-09-2018 Through 07-09-2018",

url = "http://www.eusipco2018.org",

}

Kavalekalam, MS, Nielsen, JK, Christensen, MG & Boldt, JB 2018, Model based Estimation of STP parameters for Binaural Speech Enhancement. in 2018 26th European Signal Processing Conference (EUSIPCO)., 8553145, IEEE, Proceedings of the European Signal Processing Conference, 26th European Signal Processing Conference (EUSIPCO 2018), Rome, Italy, 03/09/2018. https://doi.org/10.23919/EUSIPCO.2018.8553145

Model based Estimation of STP parameters for Binaural Speech Enhancement. / Kavalekalam, Mathew Shaji; Nielsen, Jesper Kjær; Christensen, Mads Græsbøll et al.
2018 26th European Signal Processing Conference (EUSIPCO). IEEE, 2018. 8553145 (Proceedings of the European Signal Processing Conference).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Model based Estimation of STP parameters for Binaural Speech Enhancement

AU - Kavalekalam, Mathew Shaji

AU - Nielsen, Jesper Kjær

AU - Christensen, Mads Græsbøll

AU - Boldt, Jesper Bünsow

N1 - Conference code: 26

PY - 2018

Y1 - 2018

N2 - This paper deals with the estimation of the short-term predictor (STP) parameters of speech and noise in a binaural framework. A binaural model based approach is proposed for estimating the power spectral density (PSD) of speech and noise at the individual ears for an arbitrary position of the speech source. The estimated PSDs can be subsequently used for enhancement in a binaural framework. The experimental results show that taking into account the position of the speech source using the proposed method leads to improved modelling and enhancement of the noisy speech.

AB - This paper deals with the estimation of the short-term predictor (STP) parameters of speech and noise in a binaural framework. A binaural model based approach is proposed for estimating the power spectral density (PSD) of speech and noise at the individual ears for an arbitrary position of the speech source. The estimated PSDs can be subsequently used for enhancement in a binaural framework. The experimental results show that taking into account the position of the speech source using the proposed method leads to improved modelling and enhancement of the noisy speech.

KW - autoregressive modelling, binaural speech enhancement

U2 - 10.23919/EUSIPCO.2018.8553145

DO - 10.23919/EUSIPCO.2018.8553145

M3 - Article in proceeding

SN - 978-90-827970-0-8

SN - 978-1-5386-3736-4

T3 - Proceedings of the European Signal Processing Conference

BT - 2018 26th European Signal Processing Conference (EUSIPCO)

PB - IEEE

T2 - 26th European Signal Processing Conference (EUSIPCO 2018)

Y2 - 3 September 2018 through 7 September 2018

ER -

Model based Estimation of STP parameters for Binaural Speech Enhancement

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