Abstract
In this paper we explicitly consider sentence skeleton information for Machine Translation (MT). The basic idea is that we translate the key elements of the input sentence using a skeleton translation model, and then cover the remain segments using 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 evaluation data. © 2014 Association for Computational Linguistics.
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CITATION STYLE
Xiao, T., Zhu, J., & Zhang, C. (2014). A hybrid approach to skeleton-based translation. In 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference (Vol. 2, pp. 563–568). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p14-2092
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