Paper: Minimum Bayes-Risk Decoding For Statistical Machine Translation

ACL ID N04-1022
Title Minimum Bayes-Risk Decoding For Statistical Machine Translation
Venue Human Language Technologies
Session Main Conference
Year 2004
Authors

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 de- scribe a hierarchy of loss functions that incor- porate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences. We report the performance of the MBR decoders on a Chinese-to-English trans- lation task. Our results show that MBR decod- ing can be used to tune statistical MT perfor- mance for specific loss functions.