Training hidden Markov models by hybrid simulated annealing for visual speech recognition

Jong Seok Lee, Cheol Hoon Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

This paper presents a novel training algorithm of hidden Markov models (HMMs) for visual speech recognition based on a modified simulated annealing (SA) algorithm, hybrid simulated annealing, where SA is combined with a local optimization technique to improve the convergence speed and the solution quality. While the popular training method of HMMs, the expectation-maximization (EM) algorithm, only achieves local optima in the parameter space, the proposed algorithm performs global search and thus obtains solutions giving improved recognition performance. The effectiveness of the proposed method is demonstrated via isolated word recognition experiments.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages198-202
Number of pages5
ISBN (Print)1424401003, 9781424401000
DOIs
Publication statusPublished - 2006 Jan 1
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan, Province of China
Duration: 2006 Oct 82006 Oct 11

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume1
ISSN (Print)1062-922X

Other

Other2006 IEEE International Conference on Systems, Man and Cybernetics
CountryTaiwan, Province of China
CityTaipei
Period06/10/806/10/11

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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    Lee, J. S., & Park, C. H. (2006). Training hidden Markov models by hybrid simulated annealing for visual speech recognition. In 2006 IEEE International Conference on Systems, Man and Cybernetics (pp. 198-202). [4273829] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSMC.2006.384382