IEICE TRANSACTIONS on Fundamentals
On Improving the Performance of a Speech Model-Based Blind Reverberation Time Estimation in Noisy Environments
Summary :
This paper proposes a method of improving the performance of blind reverberation time (RT) estimation in noisy environments. RT estimation is conducted using a maximum likelihood (ML) method based on the autocorrelation function of the linear predictive residual signal. To reduce the effect of environmental noise, a noise reduction technique is applied to the noisy speech signal. In addition, a frequency coefficient selection is performed to eliminate signal components with low signal-to-noise ratio (SNR). Experimental results confirm that the proposed method improves the accuracy of RT measures, particularly when the speech signal is corrupted by a colored noise with a narrow bandwidth.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E97-A No.12 pp.2688-2692
- Publication Date
- 2014/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E97.A.2688
- Type of Manuscript
- LETTER
- Category
- Measurement Technology
Authors
Tung-chin LEE
Yonsei Univ.
Young-cheol PARK
Yonsei Univ.
Dae-hee YOUN
Yonsei Univ.
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Tung-chin LEE, Young-cheol PARK, Dae-hee YOUN, "On Improving the Performance of a Speech Model-Based Blind Reverberation Time Estimation in Noisy Environments" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 12, pp. 2688-2692, December 2014, doi: 10.1587/transfun.E97.A.2688.
Abstract: This paper proposes a method of improving the performance of blind reverberation time (RT) estimation in noisy environments. RT estimation is conducted using a maximum likelihood (ML) method based on the autocorrelation function of the linear predictive residual signal. To reduce the effect of environmental noise, a noise reduction technique is applied to the noisy speech signal. In addition, a frequency coefficient selection is performed to eliminate signal components with low signal-to-noise ratio (SNR). Experimental results confirm that the proposed method improves the accuracy of RT measures, particularly when the speech signal is corrupted by a colored noise with a narrow bandwidth.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.2688/_p
Copy
@ARTICLE{e97-a_12_2688,
author={Tung-chin LEE, Young-cheol PARK, Dae-hee YOUN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={On Improving the Performance of a Speech Model-Based Blind Reverberation Time Estimation in Noisy Environments},
year={2014},
volume={E97-A},
number={12},
pages={2688-2692},
abstract={This paper proposes a method of improving the performance of blind reverberation time (RT) estimation in noisy environments. RT estimation is conducted using a maximum likelihood (ML) method based on the autocorrelation function of the linear predictive residual signal. To reduce the effect of environmental noise, a noise reduction technique is applied to the noisy speech signal. In addition, a frequency coefficient selection is performed to eliminate signal components with low signal-to-noise ratio (SNR). Experimental results confirm that the proposed method improves the accuracy of RT measures, particularly when the speech signal is corrupted by a colored noise with a narrow bandwidth.},
keywords={},
doi={10.1587/transfun.E97.A.2688},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - On Improving the Performance of a Speech Model-Based Blind Reverberation Time Estimation in Noisy Environments
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2688
EP - 2692
AU - Tung-chin LEE
AU - Young-cheol PARK
AU - Dae-hee YOUN
PY - 2014
DO - 10.1587/transfun.E97.A.2688
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2014
AB - This paper proposes a method of improving the performance of blind reverberation time (RT) estimation in noisy environments. RT estimation is conducted using a maximum likelihood (ML) method based on the autocorrelation function of the linear predictive residual signal. To reduce the effect of environmental noise, a noise reduction technique is applied to the noisy speech signal. In addition, a frequency coefficient selection is performed to eliminate signal components with low signal-to-noise ratio (SNR). Experimental results confirm that the proposed method improves the accuracy of RT measures, particularly when the speech signal is corrupted by a colored noise with a narrow bandwidth.
ER -
English
