@InProceedings{chi-EtAl:2017:I17-2,
  author    = {Chi, Ta Chung  and  Chen, Po Chun  and  Su, Shang-Yu  and  Chen, Yun-Nung},
  title     = {Speaker Role Contextual Modeling for Language Understanding and Dialogue Policy Learning},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {163--168},
  abstract  = {Language understanding (LU) and dialogue policy learning are two essential
	components in conversational systems. Human-human dialogues are not
	well-controlled and often random and unpredictable due to their own goals and
	speaking habits. This paper proposes a role-based contextual model to consider
	different speaker roles independently based on the various speaking patterns in
	the multi-turn dialogues. The experiments on the benchmark dataset show that
	the proposed role-based model successfully learns role-specific behavioral
	patterns for contextual encoding and then significantly improves language
	understanding and dialogue policy learning tasks.},
  url       = {http://www.aclweb.org/anthology/I17-2028}
}