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Shallow Syntactic Preprocessing for Statistical Machine Translation

  • Hoai-Thu Vuong
  • Dao Ngoc Tu
  • Minh Le Nguyen
  • Vinh Van Nguyen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7614)

Abstract

Reordering is of essential importance for phrase based statistical machine translation. In this paper, we would like to present a new method of reordering in phrase based statistical machine translation. We inspired from [1] using preprocessing reordering approaches. We used shallow parsing and transformation rules to reorder the source sentence. The experiment results from English-Vietnamese pair showed that our approach achieves significant improvements over MOSES which is the state-of-the art phrase based system.

Keywords

Natural Language Processing Machine Translation Phrase-based Statistical Machine Translation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hoai-Thu Vuong
    • 1
  • Dao Ngoc Tu
    • 2
  • Minh Le Nguyen
    • 3
  • Vinh Van Nguyen
    • 1
  1. 1.Computer Science DepartmentUniversity of Engineering and Technology, Vietnam National UniversityHanoiVietnam
  2. 2.Informatics FacultyHai Phong UniversityHai PhongVietnam
  3. 3.Japan Advanced Institute of Science and TechnologyNomiJapan

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