Rule-based Syntactic Preprocessing for Syntax-based Machine Translation

نویسندگان

  • Yuto Hatakoshi
  • Graham Neubig
  • Sakriani Sakti
  • Tomoki Toda
  • Satoshi Nakamura
چکیده

Several preprocessing techniques using syntactic information and linguistically motivated rules have been proposed to improve the quality of phrase-based machine translation (PBMT) output. On the other hand, there has been little work on similar techniques in the context of other translation formalisms such as syntax-based SMT. In this paper, we examine whether the sort of rule-based syntactic preprocessing approaches that have proved beneficial for PBMT can contribute to syntax-based SMT. Specifically, we tailor a highly successful preprocessing method for EnglishJapanese PBMT to syntax-based SMT, and find that while the gains achievable are smaller than those for PBMT, significant improvements in accuracy can be realized.

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تاریخ انتشار 2014