Kyoto University Participation to WAT 2017

Fabien Cromieres, Raj Dabre, Toshiaki Nakazawa, Sadao Kurohashi


Abstract
We describe here our approaches and results on the WAT 2017 shared translation tasks. Following our good results with Neural Machine Translation in the previous shared task, we continue this approach this year, with incremental improvements in models and training methods. We focused on the ASPEC dataset and could improve the state-of-the-art results for Chinese-to-Japanese and Japanese-to-Chinese translations.
Anthology ID:
W17-5714
Volume:
Proceedings of the 4th Workshop on Asian Translation (WAT2017)
Month:
November
Year:
2017
Address:
Taipei, Taiwan
Venues:
WAT | WS
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
146–153
Language:
URL:
https://www.aclweb.org/anthology/W17-5714
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-5714.pdf