@InProceedings{lin-walker:2017:StyVa,
  author    = {Lin, Grace  and  Walker, Marilyn},
  title     = {Stylistic Variation in Television Dialogue for Natural Language Generation},
  booktitle = {Proceedings of the Workshop on Stylistic Variation},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {85--93},
  abstract  = {Conversation is a critical component of storytelling, where key information is
	often revealed by
	what/how a character says it. We focus on the issue of character voice and
	build stylistic models with linguistic features related to natural language
	generation decisions. Using a dialogue corpus of the television series, The Big
	Bang Theory, we apply content analysis to extract relevant linguistic features
	to build character-based stylistic models, and we test the model-fit through an
	user perceptual experiment with Amazon's Mechanical Turk. The results are
	encouraging in that human subjects tend to perceive the generated utterances as
	being more similar to the character they are modeled on, than to another random
	character.},
  url       = {http://www.aclweb.org/anthology/W17-4911}
}