The Universitat d'Alacant Submissions to the English-to-Kazakh News Translation Task at WMT 2019
This paper describes the two submissions of Universitat d{'}Alacant to the English-to-Kazakh news translation task at WMT 2019. Our submissions take advantage of monolingual data and parallel data from other language pairs by means of iterative backtranslation, pivot backtranslation and transfer learning. They also use linguistic information in two ways: morphological segmentation of Kazakh text, and integration of the output of a rule-based machine translation system. Our systems were ranked second in terms of chrF++ despite being built from an ensemble of only 2 independent training runs.
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