@InProceedings{lee-yoon-chen:2016:PEOPLES,
  author    = {Lee, Chong Min  and  Yoon, Su-Youn  and  Chen, Lei},
  title     = {Can We Make Computers Laugh at Talks?},
  booktitle = {Proceedings of the Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {173--181},
  abstract  = {Considering the importance of public speech skills, a system which makes a
	prediction on where audiences laugh in a talk can be helpful to a person who
	prepares for a talk. We investigated a possibility that a state-of-the-art
	humor
	recognition system can be used in detecting sentences inducing laughters in
	talks. In this study, we used TED talks and laughters in the talks as data. Our
	results showed that the state-of-the-art system needs to be improved in order
	to
	be used in a practical application. In addition, our analysis showed that
	classifying humorous sentences in talks is very challenging due to close
	distance between humorous and non-humorous sentences.},
  url       = {http://aclweb.org/anthology/W16-4319}
}