A Syntax-Driven Bracketing Model for Phrase-Based Translation

نویسندگان

  • Deyi Xiong
  • Min Zhang
  • AiTi Aw
  • Haizhou Li
چکیده

Syntactic analysis influences the way in which the source sentence is translated. Previous efforts add syntactic constraints to phrase-based translation by directly rewarding/punishing a hypothesis whenever it matches/violates source-side constituents. We present a new model that automatically learns syntactic constraints, including but not limited to constituent matching/violation, from training corpus. The model brackets a source phrase as to whether it satisfies the learnt syntactic constraints. The bracketed phrases are then translated as a whole unit by the decoder. Experimental results and analysis show that the new model outperforms other previous methods and achieves a substantial improvement over the baseline which is not syntactically informed.

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تاریخ انتشار 2009