@InProceedings{guggilla:2016:VarDial3,
  author    = {Guggilla, Chinnappa},
  title     = {Discrimination between Similar Languages, Varieties and Dialects using CNN- and LSTM-based Deep Neural Networks},
  booktitle = {Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial3)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {185--194},
  abstract  = {In this paper, we describe a system (CGLI) for discriminating similar
	languages, varieties and dialects using convolutional neural networks (CNNs)
	and
	long short-term memory (LSTM) neural networks. We have participated in the
	Arabic dialect identification sub-task of DSL 2016 shared task for
	distinguishing different Arabic language texts under closed submission track.
	Our proposed approach is language independent and works for discriminating any
	given set of languages, varieties, and dialects. We have obtained 43.29%
	weighted-F1 accuracy in this sub-task using CNN approach using default network
	parameters.},
  url       = {http://aclweb.org/anthology/W16-4824}
}