Dealing with Out of Domain Questions in Virtual Characters

  • Ronakkumar Patel
  • Anton Leuski
  • David Traum
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4133)


We consider the problem of designing virtual characters that support speech-based interactions in a limited domain. Previously we have shown that classification can be an effective and robust tool for selecting appropriate in-domain responses. In this paper, we consider the problem of dealing with out-of-domain user questions. We introduce a taxonomy of out-of-domain response types. We consider three classification architectures for selecting the most appropriate out-of-domain responses. We evaluate these architectures and show that they significantly improve the quality of the response selection making the user’s interaction with the virtual character more natural and engaging.


Language Model Virtual Character Real Human Intelligent User Interface Human Coder 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chronbach, L.J.: Coefficient alpha and the internal structure of tests. Psychometrika 16, 297–333 (1951)CrossRefGoogle Scholar
  2. 2.
    Leuski, A., Pair, J., Traum, D., McNerney, P.J., Georgiou, P., Patel, R.: How to talk to a hologram. In: Edmonds, E., Riecken, D., Paris, C.L., Sidner, C.L. (eds.) Proceedings of the 11th international conference on Intelligent user interfaces (IUI 2006), Sydney, Australia, pp. 360–362. ACM Press, New York (2006)CrossRefGoogle Scholar
  3. 3.
    Leuski, A., Patel, R., Traum, D., Kennedy, B.: Building effective question answering characters. In: Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue (2006)Google Scholar
  4. 4.
    Sethy, A., Georgiou, P., Narayanan, S.: Building topic specific language models from webdata using competitive models. In: Proceedings of EUROSPEECH, Lisbon, Portugal (2005)Google Scholar
  5. 5.
    Pellom, B.: Sonic: The University of Colorado continuous speech recognizer. Technical Report TR-CSLR-2001-01, University of Colorado, Boulder, CO (2001)Google Scholar
  6. 6.
    Gandhe, S., Gordon, A.S., Traum, D.: Improving question-answering with linking dialogues. In: Proceedings of the 11th international conference on Intelligent user interfaces (IUI 2006), pp. 369–371. ACM Press, New York (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ronakkumar Patel
    • 1
  • Anton Leuski
    • 1
  • David Traum
    • 1
  1. 1.Institute for Creative TechnologiesUniversity of Southern CaliforniaMarina del ReyUSA

Personalised recommendations