@inproceedings{goto-etal-2020-neural,
title = "Neural Machine Translation Using Extracted Context Based on Deep Analysis for the {J}apanese-{E}nglish Newswire Task at {WAT} 2020",
author = "Goto, Isao and
Mino, Hideya and
Ito, Hitoshi and
Kinugawa, Kazutaka and
Yamada, Ichiro and
Tanaka, Hideki",
editor = "Nakazawa, Toshiaki and
Nakayama, Hideki and
Ding, Chenchen and
Dabre, Raj and
Kunchukuttan, Anoop and
Pa, Win Pa and
Bojar, Ond{\v{r}}ej and
Parida, Shantipriya and
Goto, Isao and
Mino, Hidaya and
Manabe, Hiroshi and
Sudoh, Katsuhito and
Kurohashi, Sadao and
Bhattacharyya, Pushpak",
booktitle = "Proceedings of the 7th Workshop on Asian Translation",
month = dec,
year = "2020",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wat-1.6",
pages = "72--79",
abstract = "This paper describes the system of the NHK-NES team for the WAT 2020 Japanese{--}English newswire task. There are two main problems in Japanese-English news translation: translation of dropped subjects and compatibility between equivalent translations and English news-style outputs. We address these problems by extracting subjects from the context based on predicate-argument structures and using them as additional inputs, and constructing parallel Japanese-English news sentences equivalently translated from English news sentences. The evaluation results confirm the effectiveness of our context-utilization method.",
}
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<abstract>This paper describes the system of the NHK-NES team for the WAT 2020 Japanese–English newswire task. There are two main problems in Japanese-English news translation: translation of dropped subjects and compatibility between equivalent translations and English news-style outputs. We address these problems by extracting subjects from the context based on predicate-argument structures and using them as additional inputs, and constructing parallel Japanese-English news sentences equivalently translated from English news sentences. The evaluation results confirm the effectiveness of our context-utilization method.</abstract>
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%0 Conference Proceedings
%T Neural Machine Translation Using Extracted Context Based on Deep Analysis for the Japanese-English Newswire Task at WAT 2020
%A Goto, Isao
%A Mino, Hideya
%A Ito, Hitoshi
%A Kinugawa, Kazutaka
%A Yamada, Ichiro
%A Tanaka, Hideki
%Y Nakazawa, Toshiaki
%Y Nakayama, Hideki
%Y Ding, Chenchen
%Y Dabre, Raj
%Y Kunchukuttan, Anoop
%Y Pa, Win Pa
%Y Bojar, Ondřej
%Y Parida, Shantipriya
%Y Goto, Isao
%Y Mino, Hidaya
%Y Manabe, Hiroshi
%Y Sudoh, Katsuhito
%Y Kurohashi, Sadao
%Y Bhattacharyya, Pushpak
%S Proceedings of the 7th Workshop on Asian Translation
%D 2020
%8 December
%I Association for Computational Linguistics
%C Suzhou, China
%F goto-etal-2020-neural
%X This paper describes the system of the NHK-NES team for the WAT 2020 Japanese–English newswire task. There are two main problems in Japanese-English news translation: translation of dropped subjects and compatibility between equivalent translations and English news-style outputs. We address these problems by extracting subjects from the context based on predicate-argument structures and using them as additional inputs, and constructing parallel Japanese-English news sentences equivalently translated from English news sentences. The evaluation results confirm the effectiveness of our context-utilization method.
%U https://aclanthology.org/2020.wat-1.6
%P 72-79
Markdown (Informal)
[Neural Machine Translation Using Extracted Context Based on Deep Analysis for the Japanese-English Newswire Task at WAT 2020](https://aclanthology.org/2020.wat-1.6) (Goto et al., WAT 2020)
ACL