@InProceedings{fung-EtAl:2016:COLINGDEMO,
  author    = {Fung, Pascale  and  Dey, Anik  and  Siddique, Farhad Bin  and  Lin, Ruixi  and  Yang, Yang  and  Bertero, Dario  and  Wan, Yan  and  Chan, Ricky Ho Yin  and  Wu, Chien-Sheng},
  title     = {Zara: A Virtual Interactive Dialogue System Incorporating Emotion, Sentiment and Personality Recognition},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {278--281},
  abstract  = {Zara, or ‘Zara the Supergirl’ is a virtual robot, that can exhibit empathy
	while interacting with an user, with the aid of its built in facial and emotion
	recognition, sentiment analysis, and speech module. At the end of the 5-10
	minute conversation, Zara can give a personality analysis of the user based on
	all the user utterances. We have also implemented a real-time emotion
	recognition, using a CNN model that detects emotion from raw audio without
	feature extraction, and have achieved an average of 65.7% accuracy on six
	different emotion classes, which is an impressive 4.5% improvement from the
	conventional feature based SVM classification. Also, we have described a CNN
	based sentiment analysis module trained using out-of-domain data, that
	recognizes sentiment from the speech recognition transcript, which has a 74.8
	F-measure when tested on human-machine dialogues.},
  url       = {http://aclweb.org/anthology/C16-2058}
}