NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task
September 19, 2018 ยท Declared Dead ยท ๐ 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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