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This paper describes the machine translation system developed jointly byBaidu Research and Oregon State University for WMT 2019 Machine TranslationRobustness Shared Task. Translation of social media is a very challengingproblem, since its style is very different from normal parallel corpora (e.g.News) and also include various types of noises. To make it worse, the amount ofsocial media parallel corpora is extremely limited. In this paper, we use adomain sensitive training method which leverages a large amount of paralleldata from popular domains together with a little amount of parallel data fromsocial media. Furthermore, we generate a parallel dataset with pseudo noisysource sentences which are back-translated from monolingual data using a modeltrained by a similar domain sensitive way. We achieve more than 10 BLEUimprovement in both En-Fr and Fr-En translation compared with the baselinemethods.

Robust Machine Translation with Domain Sensitive Pseudo-Sources: Baidu-OSU WMT19 MT Robustness Shared Task System Report