Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation

Yuki Kawara, Chenhui Chu, Yuki Arase


Abstract
The word order between source and target languages significantly influences the translation quality. Preordering can effectively address this problem. Previous preordering methods require a manual feature design, making language dependent design difficult. In this paper, we propose a preordering method with recursive neural networks that learn features from raw inputs. Experiments show the proposed method is comparable to the state-of-the-art method but without a manual feature design.
Anthology ID:
P18-3004
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:
21–27
Language:
URL:
https://aclanthology.org/P18-3004
DOI:
10.18653/v1/P18-3004
Bibkey:
Cite (ACL):
Yuki Kawara, Chenhui Chu, and Yuki Arase. 2018. Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation. In Proceedings of ACL 2018, Student Research Workshop, pages 21–27, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation (Kawara et al., ACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/P18-3004.pdf
Data
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