Paper: A Hybrid Approach to Skeleton-based Translation

ACL ID P14-2092
Title A Hybrid Approach to Skeleton-based Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

In this paper we explicitly consider sen- tence skeleton information for Machine Translation (MT). The basic idea is that we translate the key elements of the input sentence using a skeleton translation mod- el, and then cover the remain segments us- ing a full translation model. We apply our approach to a state-of-the-art phrase-based system and demonstrate very promising BLEU improvements and TER reductions on the NIST Chinese-English MT evalua- tion data.