@article{ETD,
      recid = {7640},
      author = {Meshorer, Tomer M.S.},
      title = {Using past speaker behavior to better predict turn  transitions},
      publisher = {Oregon Health and Science University},
      school = {M.S.},
      address = {2017},
      number = {ETD},
      abstract = {Conversations are at the core of everyday social  interactions. The interactions between conversants are  preformed within the realm of a sophisticated and  self-managed turn taking system. In human conversations,  the turn taking system supports minimal speaker overlap  during turn transitions and minimum gaps between turns.  Spoken dialogue systems are a new form of conversational  user interface that permits users to use their voice to  interact with the computer. As such, the turn taking  capabilities of SDS should evolve from a simple timeout to  a more human-like model. Recent advances in turn taking  systems for SDS use different local features of the last  few utterances to predict turn transition. This thesis  explores using a summary of past speaker behavior to better  predict turn transitions. We believe that the summary  features represent an evolving model of the other  conversant.},
      url = {http://digitalcollections.ohsu.edu/record/7640},
      doi = {https://doi.org/10.6083/m4j965jd},
}