Abstract
This paper describes the neural and phrase-based machine translation systems submitted by CUNI to English-Czech News Translation Task of WMT17. We experiment with synthetic data for training and try several system combination techniques, both neural and phrase-based. Our primary submission CU-CHIMERA ends up being phrase-based backbone which incorporates neural and deep-syntactic candidate translations.
Cite
CITATION STYLE
Sudarikov, R., Marecek, D., Kocmi, T., Variš, D., & Bojar, O. (2017). CUNI submission in WMT17: Chimera goes neural. In WMT 2017 - 2nd Conference on Machine Translation, Proceedings (pp. 248–256). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-4720
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
