@inproceedings{kinoshita-etal-2017-comparison,
    title = "Comparison of {SMT} and {NMT} trained with large Patent Corpora: {J}apio at {WAT}2017",
    author = "Kinoshita, Satoshi  and
      Oshio, Tadaaki  and
      Mitsuhashi, Tomoharu",
    editor = "Nakazawa, Toshiaki  and
      Goto, Isao",
    booktitle = "Proceedings of the 4th Workshop on {A}sian Translation ({WAT}2017)",
    month = nov,
    year = "2017",
    address = "Taipei, Taiwan",
    publisher = "Asian Federation of Natural Language Processing",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W17-5713/",
    pages = "140--145",
    abstract = "Japio participates in patent subtasks (JPC-EJ/JE/CJ/KJ) with phrase-based statistical machine translation (SMT) and neural machine translation (NMT) systems which are trained with its own patent corpora in addition to the subtask corpora provided by organizers of WAT2017. In EJ and CJ subtasks, SMT and NMT systems whose sizes of training corpora are about 50 million and 10 million sentence pairs respectively achieved comparable scores for automatic evaluations, but NMT systems were superior to SMT systems for both official and in-house human evaluations."
}