Presentation 1997/5/15
Pruning Algorithms for HMM On-line Handwriting Recognition
R. Kohle, T. Matsumoto,
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Abstract(in English) In large vocabulary handwriting recognition, the score evaluation of possible candidates is a considerable computational effort. In order to make handwriting recognition more feasible for practical applications, to simplify evaluation and to be able to apply discriminative training methods, we discuss various search-and pruning techniques to improve recognition speed. Based on the Viterbi algorithm, we propose a simple look-ahead pruning strategy for a sequential search and compare it with the commonly used parallel beam search. Even though the speed gain is only modest compared to the beam search, it does not affect accuracy and its simplicity is appealing. Furthermore we present a preclassification scheme, based on the stroke count, to exclude unlikely candidates from the search. Compared with a naive sequential Viterbi search, the discussed algorithms offer a significant speed improvement with none or only small degradation in accuracy.
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Keyword(in English) On-line handwriting recognition / Viterbi algorithm / Preclassification
Paper # PRMU97-5
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Conference Information
Committee PRMU
Conference Date 1997/5/15(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Pruning Algorithms for HMM On-line Handwriting Recognition
Sub Title (in English)
Keyword(1) On-line handwriting recognition
Keyword(2) Viterbi algorithm
Keyword(3) Preclassification
1st Author's Name R. Kohle
1st Author's Affiliation Department of Electrical, Electronics and Computer Engineering Waseda University()
2nd Author's Name T. Matsumoto
2nd Author's Affiliation Department of Electrical, Electronics and Computer Engineering Waseda University
Date 1997/5/15
Paper # PRMU97-5
Volume (vol) vol.97
Number (no) 40
Page pp.pp.-
#Pages 7
Date of Issue