Reducing parameter space for word alignment

  • Authors:
  • Herve Dejean;Eric Gaussier;Cyril Goutte;Kenji Yamada

  • Affiliations:
  • Xerox Research Centre Europe, Meylan, France;Xerox Research Centre Europe, Meylan, France;Xerox Research Centre Europe, Meylan, France;Xerox Research Centre Europe, Meylan, France

  • Venue:
  • HLT-NAACL-PARALLEL '03 Proceedings of the HLT-NAACL 2003 Workshop on Building and using parallel texts: data driven machine translation and beyond - Volume 3
  • Year:
  • 2003

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Abstract

This paper presents the experimental results of our attemps to reduce the size of the parameter space in word alignment algorithm. We use IBM Model 4 as a baseline. In order to reduce the parameter space, we pre-processed the training corpus using a word lemmatizer and a bilingual term extraction algorithm. Using these additional components, we obtained an improvement in the alignment error rate.