String-to-dependency statistical machine translation

  • Authors:
  • Libin Shen;Jinxi Xu;Ralph Weischedel

  • Affiliations:
  • Raytheon BBN Technologies;Raytheon BBN Technologies;Raytheon BBN Technologies

  • Venue:
  • Computational Linguistics
  • Year:
  • 2010

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Abstract

We propose a novel string-to-dependency algorithm for statistical machine translation. This algorithm employs a target dependency language model during decoding to exploit long distance word relations, which cannot be modeled with a traditional n-gram language model. Experiments show that the algorithm achieves significant improvement in MT performance over a state-of-the-art hierarchical string-to-string system on NIST MT06 and MT08 newswire evaluation sets.