@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://preview.aclanthology.org/jlcl-multiple-ingestion/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."
}