@InProceedings{toral-sanchezcartagena:2017:EACLlong,
  author    = {Toral, Antonio  and  S\'{a}nchez-Cartagena, V\'{i}ctor M.},
  title     = {A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {1063--1073},
  abstract  = {We aim to shed light on the strengths and weaknesses of the newly introduced
	neural machine translation paradigm. To that end, we conduct a multifaceted
	evaluation in which we compare outputs produced by state-of-the-art neural
	machine translation and phrase-based machine translation systems for 9 language
	directions across a number of dimensions. Specifically, we measure the
	similarity of the outputs, their fluency and amount of reordering, the effect
	of sentence length and performance across different error categories. We find
	out that translations produced by neural machine translation systems are
	considerably different, more fluent and more accurate in terms of word order
	compared to those produced by phrase-based systems. Neural machine translation
	systems are also more accurate at producing inflected forms, but they perform
	poorly when translating very long sentences.},
  url       = {http://www.aclweb.org/anthology/E17-1100}
}