A locally linear embbeding based postfiltering approach for speech enhancement

Yi Chiao Wu; Hsin Te Hwang; Syu Siang Wang; Chin Cheng Hsu; Ying Hui Lai; Yu Tsao; Hsin Min Wang

doi:10.1109/ICASSP.2017.7953219

A locally linear embbeding based postfiltering approach for speech enhancement

Yi Chiao Wu^*, Hsin Te Hwang, Syu Siang Wang, Chin Cheng Hsu, Ying Hui Lai, Yu Tsao, Hsin Min Wang

^*Corresponding author for this work

Department of Biomedical Engineering

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

5 Scopus citations

Abstract

This paper presents a novel postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enchantment (SE). The aim of the proposed LLE-based postfiltering approach is to further remove the residual noise components from the SE-processed speech signals through a spectral conversion process, thereby increasing the signal-to-noise ratio (SNR) and speech quality. The proposed postfiltering approach consists of two phases. In the offline phase, paired SE-processed and clean speech exemplars are prepared for dictionary construction. In the online phase, the LLE algorithm is adopted to convert the SE-processed speech signals to the clean ones. The present study integrates the LLE-based postfiltering approach with a deep denoising autoencoder (DDAE) SE method, which has been confirmed to provide outstanding capability for noise reduction. Experimental results show that the proposed postfiltering approach can notably enhance the DDAE-based SE processed speech signals in different noise types and SNR levels.

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	5555-5559
Number of pages	5
ISBN (Electronic)	9781509041176
DOIs	https://doi.org/10.1109/ICASSP.2017.7953219
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

deep neural network
locally linear embedding
postfiltering
Speech enhancement

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10.1109/ICASSP.2017.7953219

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Wu, Y. C., Hwang, H. T., Wang, S. S., Hsu, C. C., Lai, Y. H., Tsao, Y., & Wang, H. M. (2017). A locally linear embbeding based postfiltering approach for speech enhancement. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 5555-5559). Article 7953219 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2017.7953219

Wu, Yi Chiao ; Hwang, Hsin Te ; Wang, Syu Siang et al. / A locally linear embbeding based postfiltering approach for speech enhancement. 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 5555-5559 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

@inproceedings{b133f89d0df343a581529e2f0a549921,

title = "A locally linear embbeding based postfiltering approach for speech enhancement",

abstract = "This paper presents a novel postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enchantment (SE). The aim of the proposed LLE-based postfiltering approach is to further remove the residual noise components from the SE-processed speech signals through a spectral conversion process, thereby increasing the signal-to-noise ratio (SNR) and speech quality. The proposed postfiltering approach consists of two phases. In the offline phase, paired SE-processed and clean speech exemplars are prepared for dictionary construction. In the online phase, the LLE algorithm is adopted to convert the SE-processed speech signals to the clean ones. The present study integrates the LLE-based postfiltering approach with a deep denoising autoencoder (DDAE) SE method, which has been confirmed to provide outstanding capability for noise reduction. Experimental results show that the proposed postfiltering approach can notably enhance the DDAE-based SE processed speech signals in different noise types and SNR levels.",

keywords = "deep neural network, locally linear embedding, postfiltering, Speech enhancement",

author = "Wu, {Yi Chiao} and Hwang, {Hsin Te} and Wang, {Syu Siang} and Hsu, {Chin Cheng} and Lai, {Ying Hui} and Yu Tsao and Wang, {Hsin Min}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 ; Conference date: 05-03-2017 Through 09-03-2017",

year = "2017",

month = jun,

day = "16",

doi = "10.1109/ICASSP.2017.7953219",

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series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

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Wu, YC, Hwang, HT, Wang, SS, Hsu, CC, Lai, YH, Tsao, Y & Wang, HM 2017, A locally linear embbeding based postfiltering approach for speech enhancement. in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings., 7953219, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 5555-5559, 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.2017.7953219

A locally linear embbeding based postfiltering approach for speech enhancement. / Wu, Yi Chiao; Hwang, Hsin Te; Wang, Syu Siang et al.
2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 5555-5559 7953219 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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

TY - GEN

T1 - A locally linear embbeding based postfiltering approach for speech enhancement

AU - Wu, Yi Chiao

AU - Hwang, Hsin Te

AU - Wang, Syu Siang

AU - Hsu, Chin Cheng

AU - Lai, Ying Hui

AU - Tsao, Yu

AU - Wang, Hsin Min

PY - 2017/6/16

Y1 - 2017/6/16

N2 - This paper presents a novel postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enchantment (SE). The aim of the proposed LLE-based postfiltering approach is to further remove the residual noise components from the SE-processed speech signals through a spectral conversion process, thereby increasing the signal-to-noise ratio (SNR) and speech quality. The proposed postfiltering approach consists of two phases. In the offline phase, paired SE-processed and clean speech exemplars are prepared for dictionary construction. In the online phase, the LLE algorithm is adopted to convert the SE-processed speech signals to the clean ones. The present study integrates the LLE-based postfiltering approach with a deep denoising autoencoder (DDAE) SE method, which has been confirmed to provide outstanding capability for noise reduction. Experimental results show that the proposed postfiltering approach can notably enhance the DDAE-based SE processed speech signals in different noise types and SNR levels.

AB - This paper presents a novel postfiltering approach based on the locally linear embedding (LLE) algorithm for speech enchantment (SE). The aim of the proposed LLE-based postfiltering approach is to further remove the residual noise components from the SE-processed speech signals through a spectral conversion process, thereby increasing the signal-to-noise ratio (SNR) and speech quality. The proposed postfiltering approach consists of two phases. In the offline phase, paired SE-processed and clean speech exemplars are prepared for dictionary construction. In the online phase, the LLE algorithm is adopted to convert the SE-processed speech signals to the clean ones. The present study integrates the LLE-based postfiltering approach with a deep denoising autoencoder (DDAE) SE method, which has been confirmed to provide outstanding capability for noise reduction. Experimental results show that the proposed postfiltering approach can notably enhance the DDAE-based SE processed speech signals in different noise types and SNR levels.

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KW - locally linear embedding

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KW - Speech enhancement

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DO - 10.1109/ICASSP.2017.7953219

M3 - Conference contribution

AN - SCOPUS:85023776760

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BT - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017

Y2 - 5 March 2017 through 9 March 2017

ER -

Wu YC, Hwang HT, Wang SS, Hsu CC, Lai YH, Tsao Y et al. A locally linear embbeding based postfiltering approach for speech enhancement. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 5555-5559. 7953219. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.2017.7953219

A locally linear embbeding based postfiltering approach for speech enhancement

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