@InProceedings{cromieres-nakazawa-dabre:2017:I17-5,
  author    = {Cromieres, Fabien  and  Nakazawa, Toshiaki  and  Dabre, Raj},
  title     = {Neural Machine Translation: Basics, Practical Aspects and Recent Trends},
  booktitle = {Proceedings of the IJCNLP 2017, Tutorial Abstracts},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {11--13},
  abstract  = {Machine Translation (MT) is a sub-field of NLP which has experienced a
	number of paradigm shifts since its inception. Up until 2014, Phrase
	Based Statistical Machine Translation (PBSMT) approaches used to be
	the state of the art. In late 2014, Neural Machine Translation (NMT)
	was introduced and was proven to outperform all PBSMT approaches by a
	significant margin. Since then, the NMT approaches have undergone
	several transformations which have pushed the state of the art even
	further.
	This tutorial is primarily aimed at researchers who are either
	interested in or are fairly new to the world of NMT and want to obtain
	a deep understanding of NMT fundamentals. Because it will also cover
	the latest developments in NMT, it should also be useful to attendees
	with some experience in NMT.},
  url       = {http://www.aclweb.org/anthology/I17-5004}
}