A minimum variance partially distortionless response filter for single-channel noise reduction

Xianghui Wang; Jingdong Chen; Jacob Benesty

doi:10.1109/ICASSP.2017.7953101

A minimum variance partially distortionless response filter for single-channel noise reduction

Xianghui Wang, Jingdong Chen, Jacob Benesty

School of Marine Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper deals with the problem of single-channel noise reduction. Thanks to the eigenvalue decomposition, we arrange the eigenvalues of the speech correlation matrix in such a way that all the spectral mode signal-to-noise ratios (SNRs) of the noisy speech are ordered in a descending manner. By maintaining no speech distortion in the spectral modes with high input SNRs while allowing some degree of speech distortion in the modes with low input SNRs, we develop a minimum variance partially distortionless response (MVPDR) filter. We first formulate the problem and derive this filter within the general filtering framework. Then, the MVPDR filter is applied to the single-channel noise reduction problem in both the time and time-frequency domains. In comparison with the minimum variance distortionless response (MVDR) filter based on the subspace decomposition, the developed MVPDR filter can provide much more freedom for controlling the compromise between noise reduction and speech distortion to achieve higher speech quality. Simulations are conducted and preliminary results justify the advantages of the deduced MVPDR filter.

Original language	English
Title of host publication	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4965-4969
Number of pages	5
ISBN (Electronic)	9781509041176
DOIs	https://doi.org/10.1109/ICASSP.2017.7953101
State	Published - 16 Jun 2017
Event	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States Duration: 5 Mar 2017 → 9 Mar 2017

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)	1520-6149

Conference

Conference	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/Territory	United States
City	New Orleans
Period	5/03/17 → 9/03/17

Keywords

minimum variance partially distortionless response filter
Noise reduction
optimal linear filtering
single-channel
speech enhancement

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10.1109/ICASSP.2017.7953101

Cite this

Wang, X., Chen, J., & Benesty, J. (2017). A minimum variance partially distortionless response filter for single-channel noise reduction. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 4965-4969). Article 7953101 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2017.7953101

Wang, Xianghui ; Chen, Jingdong ; Benesty, Jacob. / A minimum variance partially distortionless response filter for single-channel noise reduction. 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 4965-4969 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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title = "A minimum variance partially distortionless response filter for single-channel noise reduction",

abstract = "This paper deals with the problem of single-channel noise reduction. Thanks to the eigenvalue decomposition, we arrange the eigenvalues of the speech correlation matrix in such a way that all the spectral mode signal-to-noise ratios (SNRs) of the noisy speech are ordered in a descending manner. By maintaining no speech distortion in the spectral modes with high input SNRs while allowing some degree of speech distortion in the modes with low input SNRs, we develop a minimum variance partially distortionless response (MVPDR) filter. We first formulate the problem and derive this filter within the general filtering framework. Then, the MVPDR filter is applied to the single-channel noise reduction problem in both the time and time-frequency domains. In comparison with the minimum variance distortionless response (MVDR) filter based on the subspace decomposition, the developed MVPDR filter can provide much more freedom for controlling the compromise between noise reduction and speech distortion to achieve higher speech quality. Simulations are conducted and preliminary results justify the advantages of the deduced MVPDR filter.",

keywords = "minimum variance partially distortionless response filter, Noise reduction, optimal linear filtering, single-channel, speech enhancement",

author = "Xianghui Wang and Jingdong Chen and Jacob Benesty",

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Wang, X, Chen, J & Benesty, J 2017, A minimum variance partially distortionless response filter for single-channel noise reduction. in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings., 7953101, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 4965-4969, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017, New Orleans, United States, 5/03/17. https://doi.org/10.1109/ICASSP.2017.7953101

A minimum variance partially distortionless response filter for single-channel noise reduction. / Wang, Xianghui; Chen, Jingdong; Benesty, Jacob.
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 4965-4969 7953101 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - This paper deals with the problem of single-channel noise reduction. Thanks to the eigenvalue decomposition, we arrange the eigenvalues of the speech correlation matrix in such a way that all the spectral mode signal-to-noise ratios (SNRs) of the noisy speech are ordered in a descending manner. By maintaining no speech distortion in the spectral modes with high input SNRs while allowing some degree of speech distortion in the modes with low input SNRs, we develop a minimum variance partially distortionless response (MVPDR) filter. We first formulate the problem and derive this filter within the general filtering framework. Then, the MVPDR filter is applied to the single-channel noise reduction problem in both the time and time-frequency domains. In comparison with the minimum variance distortionless response (MVDR) filter based on the subspace decomposition, the developed MVPDR filter can provide much more freedom for controlling the compromise between noise reduction and speech distortion to achieve higher speech quality. Simulations are conducted and preliminary results justify the advantages of the deduced MVPDR filter.

AB - This paper deals with the problem of single-channel noise reduction. Thanks to the eigenvalue decomposition, we arrange the eigenvalues of the speech correlation matrix in such a way that all the spectral mode signal-to-noise ratios (SNRs) of the noisy speech are ordered in a descending manner. By maintaining no speech distortion in the spectral modes with high input SNRs while allowing some degree of speech distortion in the modes with low input SNRs, we develop a minimum variance partially distortionless response (MVPDR) filter. We first formulate the problem and derive this filter within the general filtering framework. Then, the MVPDR filter is applied to the single-channel noise reduction problem in both the time and time-frequency domains. In comparison with the minimum variance distortionless response (MVDR) filter based on the subspace decomposition, the developed MVPDR filter can provide much more freedom for controlling the compromise between noise reduction and speech distortion to achieve higher speech quality. Simulations are conducted and preliminary results justify the advantages of the deduced MVPDR filter.

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Wang X, Chen J, Benesty J. A minimum variance partially distortionless response filter for single-channel noise reduction. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 4965-4969. 7953101. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2017.7953101

A minimum variance partially distortionless response filter for single-channel noise reduction

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