An Example-based Decoder for Spoken Language Machine Translation

نویسندگان

  • Zhoujun Li
  • Wen-Han Chao
  • Yuexin Chen
چکیده

In this paper, we propose an example-based decoder for a statistical machine translation (SMT) system, which is used for spoken language machine translation. In this way, it will help to solve the re-ordering problem and other problems for spoken language MT, such as lots of omissions, idioms etc. Through experiments, we show that this approach obtains improvements over the baseline on a Chinese-English spoken language translation task.

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تاریخ انتشار 2008