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Hybrid Algorithm for Word-Level Alignment of Parallel Texts

  • Eduardo Cendejas
  • Grettel Barceló
  • Alexander Gelbukh
  • Grigori Sidorov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5723)

Abstract

Given a text in two languages, word alignment task consists of identifying in the two variants of the text specific word occurrences that are mutual translations. The majority of existing text alignment systems follow either a linguistic or a statistical approach. We argue for that both approaches are insufficient when used separately, and suggest a flexible algorithm that combines statistical and linguistic techniques.

Keywords

Linguistic Processing Linguistic Resource Word Alignment Linguistic Approach Pointwise Mutual Information 
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.

References

  1. 1.
    Borin, L.: You’ll take the high road and i’ll take the low road: Using a third language to improve bilingual word alignment. In: ACL 2000, vol. 1, pp. 97–103 (2000)Google Scholar
  2. 2.
    Mihalca, R., Pedersen, T.: An evaluation exercise for word alignment. In: HLT-NAACL 2003 Workshop on Building and using parallel texts, vol. 3, pp. 1–10 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Eduardo Cendejas
    • 1
  • Grettel Barceló
    • 1
  • Alexander Gelbukh
    • 1
  • Grigori Sidorov
    • 1
  1. 1.Center for Computing ResearchNational Polytechnic InstituteMexico CityMexico

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