A maximum entropy approach to syntactic translation rule filtering

  • Authors:
  • Marcin Junczys-Dowmunt

  • Affiliations:
  • Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznań, Poland

  • Venue:
  • CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2010

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Abstract

In this paper we will present a maximum entropy filter for the translation rules of a statistical machine translation system based on tree transducers. This filter can be successfully used to reduce the number of translation rules by more than 70% without negatively affecting translation quality as measured by BLEU. For some filter configurations, translation quality is even improved. Our investigations include a discussion of the relationship of Alignment Error Rate and Consistent Translation Rule Score with translation quality in the context of Syntactic Statistical Machine Translation.