The N-Best Decoding Algorithm for TAT-based Translation Model

نویسندگان

  • Yun Huang
  • Qun Liu
چکیده

In this paper, we introduce a search algorithm that provides a simple and efficient way to find n-best results of the decoder of the tree-to-string alignment template (TAT) translation model, which describes the alignment between a source parse tree and a target string. Our experiments show that the new decoding algorithm does not only improve the oracle BLEU but also allow minimum error rate training procedure to find better parameters which improve the translation quality.

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تاریخ انتشار 2007