NeurAlign: combining word alignments using neural networks

  • Authors:
  • Necip Fazil Ayan;Bonnie J. Dorr;Christof Monz

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

  • Venue:
  • HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
  • Year:
  • 2005

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Abstract

This paper presents a novel approach to combining different word alignments. We view word alignment as a pattern classification problem, where alignment combination is treated as a classifier ensemble, and alignment links are adorned with linguistic features. A neural network model is used to learn word alignments from the individual alignment systems. We show that our alignment combination approach yields a significant 20--34% relative error reduction over the best-known alignment combination technique on English-Spanish and English-Chinese data.