NDLI: Some recent advances in speech recognition with potential applications in other statistical pattern recognition areas

Content Provider	IEEE Xplore Digital Library
Author	Bourlard, H.
Copyright Year	2002
Description	Author affiliation: Swiss Fed. Inst. of Technol., Lausanne, Switzerland (Bourlard, H.)
Abstract	Summary form only given. The paper reviews some recent developments in the area of statistical speech recognition, which could also be potentially useful to other statistical pattern recognition applications. Among other issues, the author discusses the use of new forms of expert mixtures, for example, the one based on the minimization of the product of error probabilities. This rule, sometimes referred to as "product-of-errors rule" has recently been used quite successfully in multi-channel (multi-modal) processing. In speech recognition, this rule was also used to implement automatically noise robust speech recognition approaches (based on frequency subband processing), which do not require noise adaptation or explicit noise models. In a related framework, he introduces the theory of "missing data", yielding significantly improved noise robustness in the case of classification of multidimensional feature vectors prone to noise in some (unknown) components. Finally, as a further generalization, he also discusses a new hidden Markov model (HMM), where the HMM emission probabilities are themselves estimated state-dependent HMMs.
File Size	28874
File Format	PDF
ISBN	076951695X
ISSN	10514651
DOI	10.1109/ICPR.2002.1048078
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech recognition Pattern recognition Hidden Markov models Noise robustness Artificial intelligence Error probability Frequency State estimation
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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