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

Yuki Kawara, Chenhui Chu, Yuki Arase

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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://preview.aclanthology.org/teach-a-man-to-fish/P18-3004.pdf
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