NDLI: Separation and robust recognition of noisy, convolutive speech mixtures using time-frequency masking and missing data techniques

Content Provider	IEEE Xplore Digital Library
Author	Kolossa, D. Klimas, A. Orglmeister, R.
Copyright Year	2005
Description	Author affiliation: Electron. & Med. Signal Process., TU Berlin (Kolossa, D.; Klimas, A.; Orglmeister, R.)
Abstract	Time-frequency masking has emerged as a powerful technique for source separation of noisy and convolved speech mixtures. It has also been applied successfully for noisy speech recognition. But while significant SNR gains are possible by adequate masking functions, speech recognition performance suffers from the involved nonlinear operations so that the greatly improved SNR often contrasts with only slight improvements in the recognition rate. To address this problem, marginalization techniques have been used for speech recognition, but they rely on speech recognition and source separation to be carried out in the same domain. However, source separation and denoising are often carried out in the short-time-Fourier-transform (STFT) domain, whereas the most useful speech recognition features are e.g. mel-frequency cepstral coefficients (MFCCs), LPC-cepstral coefficients and VQ-features. In these cases, marginalization techniques are not directly applicable. Here, another approach is suggested, which estimates sufficient statistics for speech features in the preprocessing (e.g. STFT-) domain, propagates these statistics through the transforms from the spectrum to e.g. the MFCC's of a speech recognition system and uses the estimated statistics for missing data speech recognition. With this approach, significant gains can be achieved in speech recognition rates, and in this context, time-frequency masking yields recognition rate improvements of more than 35% when compared to TF-masking based source separation
Starting Page	82
Ending Page	85
File Size	143378
Page Count	4
File Format	PDF
ISBN	0780391543
DOI	10.1109/ASPAA.2005.1540174
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Speech recognition Speech coding Time frequency analysis Source separation Statistics Noise reduction Speech enhancement Signal processing Speech processing
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
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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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