Neural Machine Translation Using Extracted Context Based on Deep Analysis for the Japanese-English Newswire Task at WAT 2020

Isao Goto, Hideya Mino, Hitoshi Ito, Kazutaka Kinugawa, Ichiro Yamada, Hideki Tanaka


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.
Anthology ID:
2020.wat-1.6
Volume:
Proceedings of the 7th Workshop on Asian Translation
Month:
December
Year:
2020
Address:
Suzhou, China
Venues:
AACL | WAT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
72–79
Language:
URL:
https://aclanthology.org/2020.wat-1.6
DOI:
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2020.wat-1.6.pdf