Improving Statistical Machine Translation with monolingual collocation

  • Authors:
  • Zhanyi Liu;Haifeng Wang;Hua Wu;Sheng Li

  • Affiliations:
  • Harbin Institute of Technology, Harbin, China;Baidu.com Inc., Beijing, China;Baidu.com Inc., Beijing, China;Harbin Institute of Technology, Harbin, China

  • Venue:
  • ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
  • Year:
  • 2010

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Abstract

This paper proposes to use monolingual collocations to improve Statistical Machine Translation (SMT). We make use of the collocation probabilities, which are estimated from monolingual corpora, in two aspects, namely improving word alignment for various kinds of SMT systems and improving phrase table for phrase-based SMT. The experimental results show that our method improves the performance of both word alignment and translation quality significantly. As compared to baseline systems, we achieve absolute improvements of 2.40 BLEU score on a phrase-based SMT system and 1.76 BLEU score on a parsing-based SMT system.