Improved HMM alignment models for languages with scarce resources

  • Authors:
  • Adam Lopez;Philip Resnik

  • Affiliations:
  • University of Maryland, College Park, MD;University of Maryland, College Park, MD

  • Venue:
  • ParaText '05 Proceedings of the ACL Workshop on Building and Using Parallel Texts
  • Year:
  • 2005

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Abstract

We introduce improvements to statistical word alignment based on the Hidden Markov Model. One improvement incorporates syntactic knowledge. Results on the workshop data show that alignment performance exceeds that of a state-of-the art system based on more complex models, resulting in over a 5.5% absolute reduction in error on Romanian-English.