@inproceedings{mino-etal-2019-neural,
title = "Neural Machine Translation System using a Content-equivalently Translated Parallel Corpus for the Newswire Translation Tasks at {WAT} 2019",
author = "Mino, Hideya and
Ito, Hitoshi and
Goto, Isao and
Yamada, Ichiro and
Tanaka, Hideki and
Tokunaga, Takenobu",
editor = "Nakazawa, Toshiaki and
Ding, Chenchen and
Dabre, Raj and
Kunchukuttan, Anoop and
Doi, Nobushige and
Oda, Yusuke and
Bojar, Ond{\v{r}}ej and
Parida, Shantipriya and
Goto, Isao and
Mino, Hidaya",
booktitle = "Proceedings of the 6th Workshop on Asian Translation",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-5212",
doi = "10.18653/v1/D19-5212",
pages = "106--111",
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.",
}
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%0 Conference Proceedings
%T Neural Machine Translation System using a Content-equivalently Translated Parallel Corpus for the Newswire Translation Tasks at WAT 2019
%A Mino, Hideya
%A Ito, Hitoshi
%A Goto, Isao
%A Yamada, Ichiro
%A Tanaka, Hideki
%A Tokunaga, Takenobu
%Y Nakazawa, Toshiaki
%Y Ding, Chenchen
%Y Dabre, Raj
%Y Kunchukuttan, Anoop
%Y Doi, Nobushige
%Y Oda, Yusuke
%Y Bojar, Ondřej
%Y Parida, Shantipriya
%Y Goto, Isao
%Y Mino, Hidaya
%S Proceedings of the 6th Workshop on Asian Translation
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F mino-etal-2019-neural
%X 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.
%R 10.18653/v1/D19-5212
%U https://aclanthology.org/D19-5212
%U https://doi.org/10.18653/v1/D19-5212
%P 106-111
Markdown (Informal)
[Neural Machine Translation System using a Content-equivalently Translated Parallel Corpus for the Newswire Translation Tasks at WAT 2019](https://aclanthology.org/D19-5212) (Mino et al., WAT 2019)
ACL