11,001 new features for statistical machine translation

  • Authors:
  • David Chiang;Kevin Knight;Wei Wang

  • Affiliations:
  • USC Information Sciences Institute, Marina del Rey, CA;USC Information Sciences Institute, Marina del Rey, CA;Language Weaver, Inc., Marina del Rey, CA

  • Venue:
  • NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
  • Year:
  • 2009

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Abstract

We use the Margin Infused Relaxed Algorithm of Crammer et al. to add a large number of new features to two machine translation systems: the Hiero hierarchical phrase-based translation system and our syntax-based translation system. On a large-scale Chinese-English translation task, we obtain statistically significant improvements of +1.5 Bleu and + 1.1 Bleu, respectively. We analyze the impact of the new features and the performance of the learning algorithm.