SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags

Eva Vanmassenhove, Andy Way

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.
Anthology ID:
P18-3010
Volume:
Proceedings of ACL 2018, Student Research Workshop
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Vered Shwartz, Jeniya Tabassum, Rob Voigt, Wanxiang Che, Marie-Catherine de Marneffe, Malvina Nissim
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
67–73
Language:
URL:
https://aclanthology.org/P18-3010
DOI:
10.18653/v1/P18-3010
Bibkey:
Cite (ACL):
Eva Vanmassenhove and Andy Way. 2018. SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags. In Proceedings of ACL 2018, Student Research Workshop, pages 67–73, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags (Vanmassenhove & Way, ACL 2018)
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