This paper describes LIMSI s submission to the first medical translation task at WMT 14. We report results for English-French on the subtask of sentence translation from summaries of medical articles. Our main submission uses a combination of NCODE (n-gram-based) and MOSES (phrase-based) output and continuous-space language models used in a post-processing step for each system. Other characteristics of our submission include: The use of sampling for building MOSES phrase table; the implementation of the vector space model proposed by Chen et al. (2013); adaptation of the POStagger used by NCODE to the medical domain; and a report of error analysis based on the typology of Vilar et al. (2006).
CITATION STYLE
Pecheux, N., Gong, L., Do, Q. K., Marie, B., Ivanishcheva, Y., Allauzen, A., … Yvon, F. (2014). LIMSI @ WMT 14 medical translation task. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 246–253). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-3330
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