NDLI: Combining VTS model compensation and support vector machines

Content Provider	IEEE Xplore Digital Library
Author	Gales, M.J.F. Flego, F.
Copyright Year	2009
Description	Author affiliation: Cambridge University Engineering Department, Trumpington St., CB2 1PZ, U.K. (Gales, M.J.F.; Flego, F.)
Abstract	It is difficult to adapt discriminative classifiers, particularly kernel based ones such as support vector machines (SVMs), to handle mismatches between the training and test data. In previous work adaptation was performed by modifying the kernel used with the SVM, rather changing the SVM parameters themselves. However an idealised form of compensation, single pass retraining, was used to alter the generative models associated with the generative kernel. In this paper vector Taylor series model compensation is used. This scheme is more efficient and allows a noise model to be estimated. The performance of the new scheme is evaluated on two continuous digit tasks. On both tasks SVM-rescoring outperformed the baseline VTS compensated models.
Starting Page	3821
Ending Page	3824
File Size	193280
Page Count	4
File Format	PDF
ISBN	9781424423538
ISSN	15206149
DOI	10.1109/ICASSP.2009.4960460
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-19
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Speech enhancement Working environment noise Hidden Markov models Kernel Acoustic noise Support vector machine classification Noise generators Taylor series Speech recognition vector Taylor series compensation speech recognition noise robustness support vector machines
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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