Neural Machine Translation System using a Content-equivalently Translated Parallel Corpus for the Newswire Translation Tasks at WAT 2019
2019-11-01WS 2019Unverified0· sign in to hype
Hideya Mino, Hitoshi Ito, Isao Goto, Ichiro Yamada, Hideki Tanaka, Takenobu Tokunaga
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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.