Interactively exploring a machine translation model

Authors:
Steve DeNeefe;Kevin Knight;Hayward H. Chan
Affiliations:
University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA
Venue:
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
Year:
2005

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Abstract

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 syntax-based decoder for themselves.