Paper: Interactive Machine Translation using Hierarchical Translation Models

ACL ID D13-1025
Title Interactive Machine Translation using Hierarchical Translation Models
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Current automatic machine translation sys- tems are not able to generate error-free trans- lations and human intervention is often re- quired to correct their output. Alternatively, an interactive framework that integrates the human knowledge into the translation pro- cess has been presented in previous works. Here, we describe a new interactive ma- chine translation approach that is able to work with phrase-based and hierarchical translation models, and integrates error-correction all in a unified statistical framework. In our experi- ments, our approach outperforms previous in- teractive translation systems, and achieves es- timated effort reductions of as much as 48% relative over a traditional post-edition system.