• DocumentCode
    3102929
  • Title

    A Hybrid Method of Chinese Prosodic Word Tagging Based on Keyword Anchor and Hidden Markov Model

  • Author

    Quan, Zhou ; Pan, Deng ; Hongjian, Liu ; Defeng, Guo ; Kenji, Nagamatsu

  • Author_Institution
    Hitachi (China) R&D Corp., Shanghai, China
  • fYear
    2009
  • fDate
    7-9 Dec. 2009
  • Firstpage
    71
  • Lastpage
    75
  • Abstract
    In this paper, a new method of Chinese prosodic word tagging is presented. This method consists of a rule-based algorithm named ¿keyword anchor¿ and a statistical algorithm based on hidden Markov model (HMM). For keyword anchor algorithm, an anchor of the prosodic word is defined to help the system to find the whole prosodic word. For statistical algorithm, a length-based hidden Markov model (HMM) is used to find the best result of prosodic word tagging. The experiments of this method prove the better result than preceding methods in this field. The ¿Open Set F Score¿ of prosodic word based on this method is up to about 0.96.
  • Keywords
    hidden Markov models; natural language processing; word processing; Chinese prosodic word tagging; Open Set F Score; hidden Markov model; keyword anchor; statistical algorithm; Hidden Markov models; Labeling; Laboratories; Large-scale systems; Natural languages; Smoothing methods; Speech synthesis; Support vector machines; Tagging; Training data; HMM; Keyword Anchor; Prosodic Word;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asian Language Processing, 2009. IALP '09. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3904-1
  • Type

    conf

  • DOI
    10.1109/IALP.2009.24
  • Filename
    5380800