Presentation 1999/12/16
Time Series Pattern Recognition by Support Vector Machine
Kouichi NAKAI, Mitsuru NAKAI, Hiroshi SHIMODAIRA, Shigeki SAGAYAMA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) We propose a new variant of Vapnik's Support Vector Machine (SVM), which can classify time series pattern such as acoustic speech data. The proposed classifier named Chain Support Vector Classifier (CSVC) consists of several SV classifiers connected in cascade. The CSVC employs an iterative learning algorithm based on Viterbi-like segmentation and the one used for the conventional SVM, though convergence has not been proven yet expect for a special case. Preliminary experiments of on-line hand-writing digits recognition showed comparable classification performance of CSVC with the single-Guassian hidden Markov models (HMM).
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Support Vector Machine / hidden Markov model / character recognition / time serise pattern
Paper # PRMU99-167
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Conference Information
Committee PRMU
Conference Date 1999/12/16(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Time Series Pattern Recognition by Support Vector Machine
Sub Title (in English)
Keyword(1) Support Vector Machine
Keyword(2) hidden Markov model
Keyword(3) character recognition
Keyword(4) time serise pattern
1st Author's Name Kouichi NAKAI
1st Author's Affiliation School of Information Science Japan Advanced Institute of Science and Technology, HOKURIKU()
2nd Author's Name Mitsuru NAKAI
2nd Author's Affiliation School of Information Science Japan Advanced Institute of Science and Technology, HOKURIKU
3rd Author's Name Hiroshi SHIMODAIRA
3rd Author's Affiliation School of Information Science Japan Advanced Institute of Science and Technology, HOKURIKU
4th Author's Name Shigeki SAGAYAMA
4th Author's Affiliation School of Information Science Japan Advanced Institute of Science and Technology, HOKURIKU
Date 1999/12/16
Paper # PRMU99-167
Volume (vol) vol.99
Number (no) 514
Page pp.pp.-
#Pages 6
Date of Issue