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.<\/p>\n
Our investigations include a discussion of the relationship of Alignment Error Rate<\/em> and Consistent Translation Rule Score<\/em> with translation quality in the context of Syntactic Statistical Machine Translation.<\/p>\n","protected":false},"excerpt":{"rendered":" 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. 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