The Resource Integrate template matching and statistical modeling for continuous speech recognition

Integrate template matching and statistical modeling for continuous speech recognition

Label
Integrate template matching and statistical modeling for continuous speech recognition
Title
Integrate template matching and statistical modeling for continuous speech recognition
Creator
Author
Subject
Language
eng
Summary
In this dissertation, a novel approach of integrating template matching with statistical modeling is proposed to improve continuous speech recognition. Commonly used Hidden Markov Models (HMMs) are ineffective in modeling details of speech temporal evolutions, which can be overcome by template-based methods. However, template-based methods are difficult to be extended in large vocabulary continuous speech recognition (LVCSR). Our proposed approach takes advantages of both statistical modeling and template matching to overcome the weaknesses of traditional HMMs and conventional template-based methods. We use multiple Gaussian Mixture Model indices to represent each frame of speech templates. The local distances of log likelihood ratio and Kullback-Leibler divergence are proposed for dynamic time warping based template matching. In order to reduce computational complexity and storage space, we propose methods of minimum distance template selection and maximum log-likelihood template selection, and investigate a template compression method on top of template selection to further improve recognition performance. Experimental results on the TIMIT phone recognition task and a LVCSR task of telehealth captioning demonstrated that the proposed approach significantly improved the performance of recognition accuracy over the HMM baselines, and on the TIMIT task, the proposed method showed consistent performance improvements over progressively enhanced HMM baselines. Moreover, the template selection methods largely reduced computation and storage complexities. Finally, an investigation was made to combine acoustic scores in triphone template matching with scores of prosodic features, which showed positive effects on vowels in LVCSR
Cataloging source
MUU
http://library.link/vocab/creatorName
Sun, Xie
Degree
Ph. D.
Dissertation note
Thesis
Dissertation year
2011.
Government publication
government publication of a state province territory dependency etc
Granting institution
University of Missouri--Columbia,
Index
no index present
Literary form
non fiction
Nature of contents
dictionaries
Label
Integrate template matching and statistical modeling for continuous speech recognition
Instantiates
Publication
Contributor
Thesis advisor
Note
Advisor: Yunxin Zhao
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Control code
872561466
Extent
1 online resource (xii, 95 pages)
Form of item
online
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Specific material designation
remote
System control number
(OCoLC)872561466
Label
Integrate template matching and statistical modeling for continuous speech recognition
Publication
Contributor
Thesis advisor
Note
Advisor: Yunxin Zhao
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Control code
872561466
Extent
1 online resource (xii, 95 pages)
Form of item
online
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Specific material designation
remote
System control number
(OCoLC)872561466

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