@InProceedings{oraby-homayon-walker:2017:StyVa,
  author    = {Oraby, Shereen  and  Homayon, Sheideh  and  Walker, Marilyn},
  title     = {Harvesting Creative Templates for Generating Stylistically Varied Restaurant Reviews},
  booktitle = {Proceedings of the Workshop on Stylistic Variation},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {28--36},
  abstract  = {Many of the creative and figurative elements that make language
	exciting are lost in translation in current natural language
	generation engines. In this paper, we explore a method to harvest
	templates from positive and negative reviews in the restaurant domain,
	with the goal of vastly expanding the types of stylistic variation
	available to the natural language generator. We learn hyperbolic
	adjective patterns that are representative of the strongly-valenced
	expressive language commonly used in either positive or negative
	reviews.  We then identify and delexicalize entities, and use
	heuristics to extract generation templates from review sentences. We
	evaluate the learned templates against more traditional review
	templates, using subjective measures of convincingness, 
	interestingness, and naturalness. Our results show that the
	learned templates score highly on these measures.  Finally, we analyze
	the linguistic categories that characterize the learned positive and
	negative templates. We plan to use the learned templates to improve the
	conversational style of dialogue systems in the
	restaurant domain.},
  url       = {http://www.aclweb.org/anthology/W17-4904}
}