@inproceedings{eriguchi-etal-2016-character,
    title = "Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation",
    author = "Eriguchi, Akiko  and
      Hashimoto, Kazuma  and
      Tsuruoka, Yoshimasa",
    editor = "Nakazawa, Toshiaki  and
      Mino, Hideya  and
      Ding, Chenchen  and
      Goto, Isao  and
      Neubig, Graham  and
      Kurohashi, Sadao  and
      Riza, Ir. Hammam  and
      Bhattacharyya, Pushpak",
    booktitle = "Proceedings of the 3rd Workshop on {A}sian Translation ({WAT}2016)",
    month = dec,
    year = "2016",
    address = "Osaka, Japan",
    publisher = "The COLING 2016 Organizing Committee",
    url = "https://preview.aclanthology.org/fix-sig-urls/W16-4617/",
    pages = "175--183",
    abstract = "This paper reports our systems (UT-AKY) submitted in the 3rd Workshop of Asian Translation 2016 (WAT{'}16) and their results in the English-to-Japanese translation task. Our model is based on the tree-to-sequence Attention-based NMT (ANMT) model proposed by Eriguchi et al. (2016). We submitted two ANMT systems: one with a word-based decoder and the other with a character-based decoder. Experimenting on the English-to-Japanese translation task, we have confirmed that the character-based decoder can cover almost the full vocabulary in the target language and generate translations much faster than the word-based model."
}