@InProceedings{kann-cotterell-schutze:2017:EACLlong,
  author    = {Kann, Katharina  and  Cotterell, Ryan  and  Sch\"{u}tze, Hinrich},
  title     = {Neural Multi-Source Morphological Reinflection},
  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     = {514--524},
  abstract  = {We explore the task of multi-source morphological reinflection, which
	generalizes the standard, single-source version. The input consists of (i) a
	target tag and (ii) multiple pairs of source form and source tag for a lemma.
	The motivation is that it is beneficial to have access to more than one source
	form since different source forms can provide complementary information, e.g.,
	different stems.  We further present a novel extension to the encoder-decoder
	recurrent neural architecture, consisting of multiple encoders, to better solve
	the task. We show
	that our new architecture outperforms single-source reinflection models and
	publish our dataset for multi-source morphological reinflection to facilitate
	future research.},
  url       = {http://www.aclweb.org/anthology/E17-1049}
}