I2r's machine translation system for IWSLT 2009

نویسندگان

  • Xiangyu Duan
  • Deyi Xiong
  • Hui Zhang
  • Min Zhang
  • Haizhou Li
چکیده

In this paper, we describe the system and approach used by the Institute for Infocomm Research (IR) for the IWSLT 2009 spoken language translation evaluation campaign. Two kinds of machine translation systems are applied, namely, phrase-based machine translation system and syntax-based machine translation system. To test syntax-based machine translation system on spoken language translation, variational systems are explored. On top of both phrase-based and syntax-based single systems, we further use rescoring method to improve the individual system performance and use system combination method to combine the strengths of the different individual systems. Rescoring is applied on each single system output, and system combination is applied on all rescoring outputs. Finally, our system combination framework shows better performance in Chinese-English BTEC task.

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تاریخ انتشار 2009