@InProceedings{ehara:2017:WAT2017,
  author    = {Ehara, Terumasa},
  title     = {SMT reranked NMT},
  booktitle = {Proceedings of the 4th Workshop on Asian Translation (WAT2017)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {119--126},
  abstract  = {System architecture, experimental settings and experimental results of the EHR
	team for the WAT2017 tasks are described. We participate in three tasks:
	JPCen-ja, JPCzh-ja and JPCko-ja. Although the basic architecture of our system
	is NMT, reranking technique is conducted using SMT results. One of the major
	drawback of NMT is under-translation and over-translation. On the other hand,
	SMT infrequently makes such translations. So, using reranking of n-best NMT
	outputs by the SMT output, discarding such translations can be expected. We can
	improve BLEU score from 46.03 to 47.08 by this technique in JPCzh-ja task.},
  url       = {http://www.aclweb.org/anthology/W17-5710}
}