NDLI: Speech enhancement using the sparse code shrinkage technique

Content Provider	IEEE Xplore Digital Library
Author	Potamitis, I. Fakotakis, N. Kokkinakis, G.
Copyright Year	2001
Description	Author affiliation: Electr. & Comput. Eng. Dept., Patras Univ., Greece (Potamitis, I.)
Abstract	Our work introduces the sparse code shrinkage (SCS) technique as a speech enhancement algorithm that aims at improving the quality of speech perception. SCS is a fairly new statistical technique originally presented to the applied mathematics and image denoising community, but, to our knowledge, its potential for speech enhancement has not yet been exploited. Its application on speech denoising gives rise to a conceptual framework which is quite different from the techniques dominating the speech enhancement domain. SCS originates in applying independent component analysis (ICA) to a large ensemble of clean speech frames, revealing their underlying basis of statistically independent functions. Projecting the frames composing a noisy speech signal on this basis, facilitates the application of Bayesian denoising to each of the resulting independent components individually. The maximum a posteriori (MAP) formulation leads to a soft threshold function optimally adapted to the statistics of each independent component which effectively reduces white and coloured Gaussian noise. Subsequently, an inverse transformation from the ICA-transformed domain back to the time domain reconstructs the enhanced signal.
Sponsorship	IEEE Signal Process. Soc
Starting Page	621
Ending Page	624
File Size	526060
Page Count	4
File Format	PDF
ISBN	0780370414
ISSN	15206149
DOI	10.1109/ICASSP.2001.940908
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-05-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech enhancement Noise reduction Independent component analysis Speech coding Mathematics Image denoising Speech analysis Bayesian methods Statistics Gaussian noise
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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