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This paper describes the University of Maryland’s submission to the WMT 2019 Kazakh to English news translation task. We study the impact of transfer learning from another lowresource but related language. We experiment with different ways of encoding lexical units to maximize lexical overlap between the two language pairs, as well as back-translation and ensembling. The submitted system improves over a Kazakh–only baseline by +5.45 BLEU on newstest2019.

The University of Maryland’s Kazakh-English Neural Machine Translation System at WMT19