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
- 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)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/P18-3010.pdf