Neural Machine Translation System using a Content-equivalently Translated Parallel Corpus for the Newswire Translation Tasks at WAT 2019

Hideya Mino, Hitoshi Ito, Isao Goto, Ichiro Yamada, Hideki Tanaka, Takenobu Tokunaga


Abstract
This paper describes NHK and NHK Engineering System (NHK-ES)’s submission to the newswire translation tasks of WAT 2019 in both directions of Japanese→English and English→Japanese. In addition to the JIJI Corpus that was officially provided by the task organizer, we developed a corpus of 0.22M sentence pairs by manually, translating Japanese news sentences into English content- equivalently. The content-equivalent corpus was effective for improving translation quality, and our systems achieved the best human evaluation scores in the newswire translation tasks at WAT 2019.
Anthology ID:
D19-5212
Volume:
Proceedings of the 6th Workshop on Asian Translation
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | WAT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
106–111
Language:
URL:
https://www.aclweb.org/anthology/D19-5212
DOI:
10.18653/v1/D19-5212
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PDF:
http://aclanthology.lst.uni-saarland.de/D19-5212.pdf