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.
@article{arxiv.1809.07037,
title = {NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task},
author = {Benjamin Marie and Rui Wang and Atsushi Fujita and Masao Utiyama and Eiichiro Sumita},
journal= {arXiv preprint arXiv:1809.07037},
year = {2018}
}
Comments
Due to the policy of our institue, with the agreement of all of the author, we decide to withdraw this paper