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
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;
Conference_Titel :
Asian Language Processing, 2009. IALP '09. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-0-7695-3904-1
DOI :
10.1109/IALP.2009.24