@inproceedings{hashimoto-etal-2016-domain,
title = "Domain Adaptation and Attention-Based Unknown Word Replacement in {C}hinese-to-{J}apanese Neural Machine Translation",
author = "Hashimoto, Kazuma and
Eriguchi, Akiko and
Tsuruoka, Yoshimasa",
editor = "Nakazawa, Toshiaki and
Mino, Hideya and
Ding, Chenchen and
Goto, Isao and
Neubig, Graham and
Kurohashi, Sadao and
Riza, Ir. Hammam and
Bhattacharyya, Pushpak",
booktitle = "Proceedings of the 3rd Workshop on {A}sian Translation ({WAT}2016)",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-4605",
pages = "75--83",
abstract = "This paper describes our UT-KAY system that participated in the Workshop on Asian Translation 2016. Based on an Attention-based Neural Machine Translation (ANMT) model, we build our system by incorporating a domain adaptation method for multiple domains and an attention-based unknown word replacement method. In experiments, we verify that the attention-based unknown word replacement method is effective in improving translation scores in Chinese-to-Japanese machine translation. We further show results of manual analysis on the replaced unknown words.",
}
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%0 Conference Proceedings
%T Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation
%A Hashimoto, Kazuma
%A Eriguchi, Akiko
%A Tsuruoka, Yoshimasa
%Y Nakazawa, Toshiaki
%Y Mino, Hideya
%Y Ding, Chenchen
%Y Goto, Isao
%Y Neubig, Graham
%Y Kurohashi, Sadao
%Y Riza, Ir. Hammam
%Y Bhattacharyya, Pushpak
%S Proceedings of the 3rd Workshop on Asian Translation (WAT2016)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F hashimoto-etal-2016-domain
%X This paper describes our UT-KAY system that participated in the Workshop on Asian Translation 2016. Based on an Attention-based Neural Machine Translation (ANMT) model, we build our system by incorporating a domain adaptation method for multiple domains and an attention-based unknown word replacement method. In experiments, we verify that the attention-based unknown word replacement method is effective in improving translation scores in Chinese-to-Japanese machine translation. We further show results of manual analysis on the replaced unknown words.
%U https://aclanthology.org/W16-4605
%P 75-83
Markdown (Informal)
[Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation](https://aclanthology.org/W16-4605) (Hashimoto et al., WAT 2016)
ACL