Paper: Translation Model Generalization using Probability Averaging for Machine Translation

ACL ID C10-1035
Title Translation Model Generalization using Probability Averaging for Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2010
Authors

Previous methods on improving transla- tion quality by employing multiple SMT models usually carry out as a second- pass decision procedure on hypotheses from multiple systems using extra fea- tures instead of using features in existing models in more depth. In this paper, we propose translation model generalization (TMG), an approach that updates proba- bility feature values for the translation model being used based on the model it- self and a set of auxiliary models, aiming to enhance translation quality in the first- pass decoding. We validate our approach on translation models based on auxiliary models built by two different ways. We also introduce novel probability variance features into the log-linear models for further improvements. We conclude that our approach can b...