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Improving Moore’s Sentence Alignment Method Using Bilingual Word Clustering

  • Hai-Long TrieuEmail author
  • Phuong-Thai Nguyen
  • Kim-Anh Nguyen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 244)

Abstract

Sentence alignment plays an extremely important role in machine translation. Most of the hybrid approaches get either a bad recall or low precision. We tackle disadvantages of several novel sentence alignment approaches, which combine length-based and word correspondences. Word clustering is applied in our method in order to improve the quality of the sentence aligner, especially when dealing with the sparse data problem. Our approach overcomes the limits of previous hybrid methods and obtains both highly recall and reasonable precision rates.

Keywords

Word Pair Machine Translation Recall Rate Translation Model Statistical Machine Translation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hai-Long Trieu
    • 1
    Email author
  • Phuong-Thai Nguyen
    • 2
  • Kim-Anh Nguyen
    • 3
  1. 1.Faculty of MathematicsThai Nguyen University of EducationThainguyenVietnam
  2. 2.University of Engineering and Technology, Vietnam National UniversityHanoiVietnam
  3. 3.Faculty of Mathematics and TechnologyHung Vuong UniversityPhuthoVietnam

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