@InProceedings{aharoni-goldberg:2017:Long,
  author    = {Aharoni, Roee  and  Goldberg, Yoav},
  title     = {Morphological Inflection Generation with Hard Monotonic Attention},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {2004--2015},
  abstract  = {We present a neural model for morphological inflection generation which employs
	a hard attention mechanism, inspired by the nearly-monotonic alignment commonly
	found between the characters in a word and the characters in its inflection. We
	evaluate the model on three previously studied morphological inflection
	generation datasets and show that it provides state of the art results in
	various setups compared to previous neural and non-neural approaches. Finally
	we present an analysis of the continuous representations learned by both the
	hard and soft (Bahdanau, 2014) attention models for the task, shedding some
	light on the features such models extract.},
  url       = {http://aclweb.org/anthology/P17-1183}
}