NDLI: Statistical models for speech dereverberation

Content Provider	IEEE Xplore Digital Library
Author	Yoshioka, T. Kameoka, H. Nakatani, T. Okuno, H.G.
Copyright Year	2009
Description	Author affiliation: Graduate School of Informatics, Kyoto University, Yoshida-hommachi, Sakyo-ku, 606-8501, Japan (Okuno, H.G.) \|\| NTT Communication Science Laboratories, NTT Corporation, 2-4, Hikari-dai, Seika-cho, Soraku-gun, Kyoto 619-0237, Japan (Yoshioka, T.; Kameoka, H.; Nakatani, T.)
Abstract	This paper discusses a statistical-model-based approach to speech dereverberation. With this approach, we first define parametric statistical models of probability density functions (pdfs) for a clean speech signal and a room transmission channel, then estimate the model parameters, and finally recover the clean speech signal by using the pdfs with the estimated parameter values. The key to the success of this approach lies in the definition of the models of the clean speech signal and room transmission channel pdfs. This paper presents several statistical models (including newly proposed ones) and compares them in a large-scale experiment. As regards the room transmission channel pdf, an autoregressive (AR) model, an autoregressive power spectral density (ARPSD) model, and a moving-average power spectral density (MAPSD) model are considered. A clean speech signal pdf model is selected according to the room transmission channel pdf model. The AR model exhibited the highest dereverberation accuracy when a reverberant speech signal of 2 sec or longer was available while the other two models outperformed the AR model when only a 1-sec reverberant speech signal was available.
Starting Page	145
Ending Page	148
File Size	1072420
Page Count	4
File Format	PDF
ISBN	9781424436781
ISSN	19311168
DOI	10.1109/ASPAA.2009.5346489
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech processing Speech enhancement Acoustics Parameter estimation Reverberation Noise reduction Probability density function Degradation Microphones Frequency statistical model Dereverberation
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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