@InProceedings{eriguchi-hashimoto-tsuruoka:2016:WAT2016,
  author    = {Eriguchi, Akiko  and  Hashimoto, Kazuma  and  Tsuruoka, Yoshimasa},
  title     = {Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation},
  booktitle = {Proceedings of the 3rd Workshop on Asian Translation (WAT2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  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.},
  url       = {http://aclweb.org/anthology/W16-4617}
}