User Modeling & Spoken Dialog Management

Professor: Shrikanth Narayanan

Phd. students: JongHo Shin, Abe Kazemzadeh, Viktor Rozgic

Conversational interfaces hold the promise of providing natural, easy and universal access to information. The research effort of this project targets two specific problems in conversational engineering under a unifying stochastic modeling framework:

User models are essential in designing optimal dialog strategies, while discourse state information is essential for user behavior modeling. Conversational participants -- humans or machines -- are modeled as stochastic dynamical systems, interacting with one another over a noisy communication channel.

The approach to modeling user behavior is data-driven with an emphasis on behavior under error conditions and on the inclusion of automatic emotion tracking. An unified statistical framework provides a way for integrating multiple sources of information (e.g., acoustic, lexical, nonverbal and discourse) based on information-theoretic principles.

Current projects

            * NSF: National Science Foundation, IMSC: Integrated Media Systems Center, ICT: Institute for Creative Technologies.

Selected publication

 

Annotation scheme for tagging communicator data

- model tags

© 2005 Speech Analysis and Interpretation Laboratory, USC
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