@InProceedings{kinoshita-EtAl:2016:WAT2016,
  author    = {Kinoshita, Satoshi  and  Oshio, Tadaaki  and  Mitsuhashi, Tomoharu  and  Ehara, Terumasa},
  title     = {Translation Using JAPIO Patent Corpora: JAPIO at WAT2016},
  booktitle = {Proceedings of the 3rd Workshop on Asian Translation (WAT2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {133--138},
  abstract  = {We participate in scientific paper subtask (ASPEC-EJ/CJ) and patent subtask
	(JPC-EJ/CJ/KJ) with phrase-based SMT systems which are trained with its own
	patent corpora.  Using larger corpora than those prepared by the workshop
	organizer, we achieved higher BLEU scores than most participants in EJ and CJ
	translations of patent subtask, but in crowdsourcing evaluation, our EJ
	translation, which is best in all automatic evaluations, received a very poor
	score.                    In scientific paper subtask, our translations are given
	lower
	scores
	than most translations that are produced by translation engines trained with
	the in-domain corpora.                    But our scores are higher than those of
	general-purpose
	RBMTs and online services.  Considering the result of crowdsourcing evaluation,
	it shows a possibility that CJ SMT system trained with a large patent corpus
	translates non-patent technical documents at a practical level.},
  url       = {http://aclweb.org/anthology/W16-4612}
}