NDLI: Speech Enhancement Using Modified Modulation Magnitude Estimation-Based Spectral Subtraction Algorithm

Content Provider	Springer Nature Link
Author	Kalamani, M. Valarmathy, S. Krishnamoorthi, M.
Copyright Year	2014
Abstract	In this paper, noise variance is estimated from the noisy spectrum using the proposed noise estimation algorithm. In addition, the speech signal is enhanced by the modified modulation magnitude estimation (MMME)-based spectral subtraction algorithm. Chi-square distribution-based noise estimation algorithm is proposed in this work. During the speech presence period, the noise variance is estimated by recursively smoothing and averaging the noisy spectrum. The speech signal is then enhanced by estimating the modulation magnitude spectrum, which depends on a posterior SNR instead of a priori SNR. The optimal speech presence probability q $_{ m }$ is found as 0.9, and simulations are carried out for this optimal value. Objective and subjective measures for the various noises are made and compared between the existing and proposed algorithms. From the experimental results, it is observed that the proposed noise estimation method comparably reduces mean square error (MSE) and LogErr to the earlier methods under various noise conditions with different input SNR levels. In addition, the proposed spectral subtraction method noticeably increases the dB value of peak signal to noise ratio, segmental SNR and segmental SNR improvement (ΔSNR$_{seg}$) contrasting various existing spectral subtraction algorithms with the optimal q $_{ m }$ value. Also, it improves the mean opinion score value and reduces the log spectral distance and MSE when compared to that of various existing ones. Hence, it reveals that the MMME-based spectral subtraction with proposed noise estimation algorithm reduces the speech distortion and residual noise as compared to existing methods.
Starting Page	8965
Ending Page	8978
Page Count	14
File Format	PDF
ISSN	13198025
Journal	Arabian Journal for Science and Engineering
Volume Number	39
Issue Number	12
e-ISSN	21914281
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-11-13
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Speech enhancement Noise estimation Speech distortion Residual noise Speech quality Spectral subtraction Engineering Science
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
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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