@inproceedings{kawara-etal-2018-recursive,
title = "Recursive Neural Network Based Preordering for {E}nglish-to-{J}apanese Machine Translation",
author = "Kawara, Yuki and
Chu, Chenhui and
Arase, Yuki",
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/P18-3004",
doi = "10.18653/v1/P18-3004",
pages = "21--27",
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.",
}
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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.</abstract>
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%0 Conference Proceedings
%T Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation
%A Kawara, Yuki
%A Chu, Chenhui
%A Arase, Yuki
%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 kawara-etal-2018-recursive
%X 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.
%R 10.18653/v1/P18-3004
%U https://aclanthology.org/P18-3004
%U https://doi.org/10.18653/v1/P18-3004
%P 21-27
Markdown (Informal)
[Recursive Neural Network Based Preordering for English-to-Japanese Machine Translation](https://aclanthology.org/P18-3004) (Kawara et al., ACL 2018)
ACL