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Spoken Networks

The Spoken Networks projects studies how real-world, face-to-face social behavior can be measured and modeled in ways that simultaneously protect privacy and provide new insight into the dynamics of human social behavior.

Publications

  • Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models (2010)
  • Dynamic Multi-Valued Network Models for Predicting Face-to-Face Conversations (2009)
  • Collective Modeling of Human Social Behavior (2009)
  • Towards the Automated Social Analysis of Situated Speech Data (2008)
  • Learning Hidden Curved Exponential Random Graph Models to Infer Face-to-Face Interaction Networks from Situated Speech Data (2008)
  • Creating Social Network Models from Sensor Data (2007)
  • Conversation Detection and Speaker Segmentation in Privacy-Sensitive Situated Speech Data (2007)
  • Capturing Spontaneous Conversation and Social Dynamics: A Privacy Sensitive Data Collection Effort (2007)
  • A Privacy-Sensitive Approach to Modeling Multi-Person Conversations (2007)

Research Groups

  • Artificial Intelligence
  • Machine Learning
Last changed Fri, 2012-11-16 11:28
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Computer Science & Engineering   University of Washington   Box 352350   Seattle, WA 98195-2350   (206) 543-1695 voice, (206) 543-2969 FAX   

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