@InProceedings{jagfeld-vu:2017:Speech-Centric,
  author    = {Jagfeld, Glorianna  and  Vu, Ngoc Thang},
  title     = {Encoding Word Confusion Networks with Recurrent Neural Networks for Dialog State Tracking},
  booktitle = {Proceedings of the Workshop on Speech-Centric Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {10--17},
  abstract  = {This paper presents our novel method to encode word confusion networks, which
	can represent a rich hypothesis space of automatic speech recognition systems,
	via recurrent neural networks.
	We demonstrate the utility of our approach for the task of dialog state
	tracking in spoken dialog systems that relies on automatic speech recognition
	output.
	Encoding confusion networks outperforms encoding the best hypothesis of the
	automatic speech recognition in a neural system for dialog state tracking on
	the well-known second Dialog State Tracking Challenge dataset.},
  url       = {http://www.aclweb.org/anthology/W17-4602}
}