Posture, Relationship, and Discourse Structure

Models of Nonverbal Behavior for Long-Term Interaction
  • Daniel Schulman
  • Timothy Bickmore
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6895)


We present an empirical investigation of nonverbal behavior in long-term interaction spanning multiple conversations, in the context of a developing interpersonal relationship. Based on a longitudinal video corpus of human-human counseling conversation, we develop a model of the occurrence of posture shifts which incorporates changes that occur both within a single conversation and over multiple conversations. Implications for the design and implementation of virtual agents are discussed, with a particular focus on agents designed for long-term interaction.


relational agent embodied conversational agent nonverbal behavior relationship posture discourse structure 


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  1. 1.
    Andersen, P.A.: Nonverbal immediacy in interpersonal communication. In: Siegman, A.W., Feldstein, S. (eds.) Multichannel Integrations of Nonverbal Behavior, pp. 1–36. Lawrence Erlbaum, Hillsdale (1985)Google Scholar
  2. 2.
    Bates, D., Maechler, M., Bolker, B.: lme4: Linear mixed-effects models using S4 classes (2011),, R package version 0.999375-39
  3. 3.
    Bernieri, F.J.: Coordinated movement and rapport in teacher-student interactions. Journal of Nonverbal Behavior 12(2), 120–138 (1988)CrossRefGoogle Scholar
  4. 4.
    Bickmore, T.: Relational Agents: Effecting Change through Human-Computer Relationships. Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA (2003)Google Scholar
  5. 5.
    Bickmore, T., Schulman, D., Yin, L.: Maintaining engagement in long-term interventions with relational agents. Applied Artificial Intelligence 24(6), 648–666 (2010)CrossRefGoogle Scholar
  6. 6.
    Bozdogan, H.: Model selection and Akaike’s Information Criterion (AIC): The general theory and its analytical extensions. Psychometrika 52(3), 345–370 (1987)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Cassell, J., Gill, A.J., Tepper, P.A.: Coordination in conversation and rapport. In: Workshop on Embodied Language Processing, pp. 41–50. Association for Computational Linguistics (June 2007)Google Scholar
  8. 8.
    Cassell, J., Nakano, Y.I., Bickmore, T.W., Sidner, C.L., Rich, C.: Non-verbal cues for discourse structure. In: ACL 2001: Proceedings of the 39th Annual Meeting on Association for Computational Linguistics, pp. 114–123. Association for Computational Linguistics, Morristown (2001)CrossRefGoogle Scholar
  9. 9.
    Cassell, J., Vilhjálmsson, H.H., Bickmore, T.: BEAT: the Behavior Expression Animation Toolkit. In: SIGGRAPH 2001: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 477–486. ACM, New York (2001)CrossRefGoogle Scholar
  10. 10.
    Grosz, B.J., Sidner, C.L.: Attention, intentions, and the structure of discourse. Computational Linguistics 12(3), 175–204 (1986)Google Scholar
  11. 11.
    Hatcher, R.L., Gillaspy, A.J.: Development and validation of a revised short version of the Working Alliance Inventory. Psychotherapy Research 16(1), 12–25 (2006)CrossRefGoogle Scholar
  12. 12.
    Kendon, A.: Some relationships between body motion and speech. In: Seigman, A., Pope, B. (eds.) Studies in Dyadic Communication, pp. 177–216. Pergamon Press, Elmsford (1972)Google Scholar
  13. 13.
    Lafrance, M.: Nonverbal synchrony and rapport: Analysis by the Cross-Lag panel technique. Social Psychology Quarterly 42(1), 66–70 (1979)CrossRefGoogle Scholar
  14. 14.
    LaFrance, M., Ickes, W.: Posture mirroring and interactional involvement: Sex and sex typing effects. Journal of Nonverbal Behavior 5(3), 139–154 (1981)CrossRefGoogle Scholar
  15. 15.
    Martin, D.J., Garske, J.P., Davis, M.K.: Relation of the therapeutic alliance with outcome and other variables: a meta-analytic review. Journal of Consulting and Clinical Psychology 68(3), 438–450 (2000)CrossRefGoogle Scholar
  16. 16.
    McCulloch, C.E., Neuhaus, J.M.: Generalized Linear Mixed Models. John Wiley & Sons, Ltd., Chichester (2005)Google Scholar
  17. 17.
    R Development Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2011),, ISBN 3-900051-07-0
  18. 18.
    Scheflen, A.E.: The significance of posture in communication systems. Psychiatry 27, 316–331 (1964)Google Scholar
  19. 19.
    Schulman, D., Bickmore, T.: Modeling behavioral manifestations of coordination and rapport over multiple conversations. In: Allbeck, J., Badler, N., Bickmore, T., Pelachaud, C., Safonova, A. (eds.) IVA 2010. LNCS, vol. 6356, pp. 132–138. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  20. 20.
    Tickle-Degnen, L., Gavett, E.: Changes in nonverbal behavior during the development of therapeutic relationships. In: Philippot, P., Feldman, R.S., Coats, E.J. (eds.) Nonverbal Behavior in Clinical Settings, ch. 4, pp. 75–110. Oxford University Press, New York (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Daniel Schulman
    • 1
  • Timothy Bickmore
    • 1
  1. 1.College of Computer and Information ScienceNortheastern UniversityBostonUSA

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