Interactively Exploring a Machine Translation Model

نویسندگان

  • Steve DeNeefe
  • Kevin Knight
  • Hayward H. Chan
چکیده

This paper describes a method of interactively visualizing and directing the process of translating a sentence. The method allows a user to explore a model of syntax-based statistical machine translation (MT), to understand the model’s strengths and weaknesses, and to compare it to other MT systems. Using this visualization method, we can find and address conceptual and practical problems in an MT system. In our demonstration at ACL, new users of our tool will drive a syntaxbased decoder for themselves.

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تاریخ انتشار 2005