@inproceedings{vanmassenhove-way-2018-supernmt,
title = "{S}uper{NMT}: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags",
author = "Vanmassenhove, Eva and
Way, Andy",
editor = "Shwartz, Vered and
Tabassum, Jeniya and
Voigt, Rob and
Che, Wanxiang and
de Marneffe, Marie-Catherine and
Nissim, Malvina",
booktitle = "Proceedings of {ACL} 2018, Student Research Workshop",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-3010",
doi = "10.18653/v1/P18-3010",
pages = "67--73",
abstract = "In this paper we incorporate semantic supersensetags and syntactic supertag features into EN{--}FR and EN{--}DE factored NMT systems. In experiments on various test sets, we observe that such features (and particularly when combined) help the NMT model training to converge faster and improve the model quality according to the BLEU scores.",
}
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<abstract>In this paper we incorporate semantic supersensetags and syntactic supertag features into EN–FR and EN–DE factored NMT systems. In experiments on various test sets, we observe that such features (and particularly when combined) help the NMT model training to converge faster and improve the model quality according to the BLEU scores.</abstract>
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%0 Conference Proceedings
%T SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags
%A Vanmassenhove, Eva
%A Way, Andy
%Y Shwartz, Vered
%Y Tabassum, Jeniya
%Y Voigt, Rob
%Y Che, Wanxiang
%Y de Marneffe, Marie-Catherine
%Y Nissim, Malvina
%S Proceedings of ACL 2018, Student Research Workshop
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F vanmassenhove-way-2018-supernmt
%X In this paper we incorporate semantic supersensetags and syntactic supertag features into EN–FR and EN–DE factored NMT systems. In experiments on various test sets, we observe that such features (and particularly when combined) help the NMT model training to converge faster and improve the model quality according to the BLEU scores.
%R 10.18653/v1/P18-3010
%U https://aclanthology.org/P18-3010
%U https://doi.org/10.18653/v1/P18-3010
%P 67-73
Markdown (Informal)
[SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags](https://aclanthology.org/P18-3010) (Vanmassenhove & Way, ACL 2018)
ACL