LIMSI $@$ WMT'14 Medical Translation Task

This paper describes LIMSI’s submission to the first medical translation task at WMT’14. We report results for EnglishFrench 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).