@InProceedings{xu-reitter:2017:Long,
  author    = {Xu, Yang  and  Reitter, David},
  title     = {Spectral Analysis of Information Density in Dialogue Predicts Collaborative Task Performance},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {623--633},
  abstract  = {We propose a perspective on dialogue that focuses on relative information
	contributions of conversation partners as a key to successful communication. We
	predict the success of collaborative task in English and Danish corpora of
	task-oriented dialogue. Two features are extracted from the frequency domain
	representations of  the lexical entropy series of each interlocutor, power
	spectrum overlap (PSO) and relative phase (RP). We find that PSO is a negative
	predictor of task success, while RP is a positive one. An SVM with these
	features significantly improved on previous task success prediction models. Our
	findings suggest that the strategic distribution of information density between
	interlocutors  is relevant to task success.},
  url       = {http://aclweb.org/anthology/P17-1058}
}