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We present Minimum Bayes-Risk word alignment for machine translation. This statistical, model-based approach attempts to minimize the expected risk of align- ment errors under loss functions that mea- sure alignment …...

We present Minimum Bayes-Risk (MBR) de- coding for statistical machine translation. This statistical approach aims to minimize expected loss of translation errors under loss functions that measure translation performance. We …...

We present Minimum Bayes-Risk (MBR) de- coding over translation lattices that compactly encode a huge number of translation hypothe- ses. We describe conditions on the loss func- tion that will …...

This paper describes the Aalto submission for the German-to-English and the Czech- to-English translation tasks of the ACL 2010 Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR. Statistical machine …...

We present minimum Bayes-risk system com- bination, a method that integrates consen- sus decoding and system combination into a unified multi-system minimum Bayes-risk (MBR) technique. Unlike other MBR meth- ods …...

This paper implements and compares three different strategies to use English as pivot language for Chinese-Japanese patent translation: corpus enrichment, sentence pivot translation and phrase pivot translation. Our results show …...

AbstractIn Neural Machine Translation, it is typically assumed that the sentence with the highest estimated probability should also be the translation with the highest quality as measured by humans. In …...