• DocumentCode
    3489933
  • Title

    Modality-Preserving Phrase-Based Statistical Machine Translation

  • Author

    Ideue, M. ; Yamamoto, Koji ; Utiyama, M. ; Sumita, Eiichiro

  • Author_Institution
    Dept. of Electr. Eng., Nagaoka Univ. of Technol., Nagaoka, Japan
  • fYear
    2012
  • fDate
    13-15 Nov. 2012
  • Firstpage
    129
  • Lastpage
    132
  • Abstract
    In machine translation (MT), modality errors are often critical. We propose a phrase-based statistical MT method that preserves the modality of input sentences. The method introduces a feature function that counts the number of phrases in a sentence that are characteristic words for modalities. This simple method increases the number of translations that have the same modality as the input sentences.
  • Keywords
    language translation; natural language processing; text analysis; feature function; input sentences; modality errors; modality preservation; modality-preserving phrase-based statistical machine translation; phrase-based statistical MT method; Accuracy; Equations; Feature extraction; Manuals; Mathematical model; Training; Training data; modality; statistical machine translation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Asian Language Processing (IALP), 2012 International Conference on
  • Conference_Location
    Hanoi
  • Print_ISBN
    978-1-4673-6113-2
  • Electronic_ISBN
    978-0-7695-4886-9
  • Type

    conf

  • DOI
    10.1109/IALP.2012.50
  • Filename
    6473713