Fluency Constraints for Minimum Bayes-Risk Decoding of Statistical Machine Translation Lattices
Graeme Blackwood, Adrià de Gispert, Bill Byrne · Cambridge University Engineering Department Publications Database · 2010
A novel and robust approach to improving statistical machine translation fluency is developed within a minimum Bayes-risk decoding framework. By segmenting translation lattices according to confidence measures over the maximum likelihood translation hypothesis we are able to focus on regions with potential translation errors. Hypothesis space constraints based on monolingual coverage are applied to the low confidence regions to improve overall translation fluency. 1