NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task

September 19, 2018 ยท Declared Dead ยท ๐Ÿ› Conference on Machine Translation

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Authors Benjamin Marie, Rui Wang, Atsushi Fujita, Masao Utiyama, Eiichiro Sumita arXiv ID 1809.07037 Category cs.CL: Computation & Language Citations 21 Venue Conference on Machine Translation Last Checked 4 months ago
Abstract
This paper presents the NICT's participation to the WMT18 shared news translation task. We participated in the eight translation directions of four language pairs: Estonian-English, Finnish-English, Turkish-English and Chinese-English. For each translation direction, we prepared state-of-the-art statistical (SMT) and neural (NMT) machine translation systems. Our NMT systems were trained with the transformer architecture using the provided parallel data enlarged with a large quantity of back-translated monolingual data that we generated with a new incremental training framework. Our primary submissions to the task are the result of a simple combination of our SMT and NMT systems. Our systems are ranked first for the Estonian-English and Finnish-English language pairs (constraint) according to BLEU-cased.
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