• DocumentCode
    3141556
  • Title

    Naxi-English bilingual word alignment based on language feature model of Naxi

  • Author

    Yu, Zhengtao ; Zhang, Tao ; Guo, Jianyi ; Mao, Cunli ; Li, Jian

  • Author_Institution
    Sch. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
  • fYear
    2011
  • fDate
    27-29 Nov. 2011
  • Firstpage
    100
  • Lastpage
    105
  • Abstract
    To achieve the corpus of Naxi - English bilingual words alignment, aim at syntactic characteristics of Naxi language. A Naxi-English bilingual words alignment method is proposed. This method uses the log-linear model, and introduces feature functions based on the characteristic of the Naxi language, which are English - Naxi interval switching function and Naxi - English bilingual words position transformation function. With the artificial labeling of Naxi - English words alignment corpus, the parameters of the model are trained by using the minimum error. The Naxi-English bilingual words are alignment automatically by this model. Experiments with IBM Model 3 as a benchmark, and gradually add constraints on the characteristics of the Naxi language with the basis of IBM Model 3. The final experiment results show that the Naxi - English bilingual word alignment accuracy can be improved significantly with the feature functions which are base on characteristic of Naxi.
  • Keywords
    natural language processing; English-Naxi interval switching function; IBM Model 3; Naxi-English bilingual word alignment; Naxi-English bilingual words position transformation function; Naxi-English words alignment corpus; feature functions; language feature model; log-linear model; Accuracy; Training; English; Naxi language; feature functions; interval switching function; log-linear model; position transformation function; word alignment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Language Processing andKnowledge Engineering (NLP-KE), 2011 7th International Conference on
  • Conference_Location
    Tokushima
  • Print_ISBN
    978-1-61284-729-0
  • Type

    conf

  • DOI
    10.1109/NLPKE.2011.6138176
  • Filename
    6138176