Combination of statistical word alignments based on multiple preprocessing schemes

  • Authors:
  • Jakob Elming;Nizar Habash

  • Affiliations:
  • Copenhagen Business School;Columbia University

  • Venue:
  • NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
  • Year:
  • 2007

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Abstract

We present an approach to using multiple preprocessing schemes to improve statistical word alignments. We show a relative reduction of alignment error rate of about 38%.