Conversational Behavior Reflecting Interpersonal Attitudes in Small Group Interactions

  • Brian Ravenet
  • Angelo Cafaro
  • Beatrice Biancardi
  • Magalie Ochs
  • Catherine Pelachaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9238)


In this paper we propose a computational model for the real time generation of nonverbal behaviors supporting the expression of interpersonal attitudes for turn-taking strategies and group formation in multi-party conversations among embodied conversational agents. Starting from the desired attitudes that an agent aims to express towards every other participant, our model produces the nonverbal behavior that should be exhibited in real time to convey such attitudes while managing the group formation and attempting to accomplish the agent’s own turn-taking strategy. We also propose an evaluation protocol for similar multi-agent configurations. We conducted a study following this protocol to evaluate our model. Results showed that subjects properly recognized the attitudes expressed by the agents through their nonverbal behavior and turn taking strategies generated by our system.


Nonverbal Behavior Body Orientation Group Engagement Virtual Agent Repeated Measure MANOVA 
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.



This work was partially was performed within the Labex SMART (ANR-11-LABX-65) supported by French state funds managed by the ANR within the Investissements d’Avenir programme under reference ANR-11-IDEX-0004-02. It has also been partially funded by the French National Research Agency project MOCA (ANR-12-CORD-019) and by the H2020 European project ARIA-VALUSPA.


  1. 1.
    Argyle, M.: Bodily Communication. University Paperbacks, Methuen (1988)Google Scholar
  2. 2.
    Beebe, S.A., Masterson, J.T.: Communication in Small Groups: Principles and Practices. Pearson Education, Inc., Boston (2009)Google Scholar
  3. 3.
    Cafaro, A., Vilhjálmsson, H.H., Bickmore, T., Heylen, D., Jóhannsdóttir, K.R., Valgarosson, G.S.: First impressions: users’ judgments of virtual agents’ personality and interpersonal attitude in first encounters. In: Nakano, Y., Neff, M., Paiva, A., Walker, M. (eds.) IVA 2012. LNCS, vol. 7502, pp. 67–80. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  4. 4.
    Callejas, Z., Ravenet, B., Ochs, M., Pelachaud, C.: A computational model of social attitudes for a virtual recruiter. In: Autonomous Agent and Multiagent Systems (2014)Google Scholar
  5. 5.
    Cappella, J.N., Siegman, A.W., Feldstein, S.: Controlling the floor in conversation. In: Siegman, A.W., Feldstein, S. (eds.) Multichannel Integrations of Nonverbal Behavior, pp. 69–103. Erlbaum, Hillsdale (1985)Google Scholar
  6. 6.
    Chollet, M., Ochs, M., Pelachaud, C.: From non-verbal signals sequence mining to Bayesian networks for interpersonal attitudes expression. In: Bickmore, T., Marsella, S., Sidner, C. (eds.) IVA 2014. LNCS, vol. 8637, pp. 120–133. Springer, Heidelberg (2014) Google Scholar
  7. 7.
    Clark, H.H.: Using Language. Cambridge University Press, Cambridge (1996) CrossRefGoogle Scholar
  8. 8.
    Cristani, M., Paggetti, G., Vinciarelli, A., Bazzani, L., Menegaz, G., Murino, V.: Towards computational proxemics: inferring social relations from interpersonal distances. In: Privacy, Security, Risk and Trust, pp. 290–297. IEEE (2011)Google Scholar
  9. 9.
    Duncan, S.: Some signals and rules for taking speaking turns in conversations. J. Pers. Soc. Psychol. 23(2), 283 (1972)CrossRefGoogle Scholar
  10. 10.
    Gillies, M., Crabtree, I.B., Ballin, D.: Customisation and context for expressive behaviour in the broadband world. BT Technol. J. 22(2), 7–17 (2004)CrossRefGoogle Scholar
  11. 11.
    Goffman, E.: Forms of Talk. University of Pennsylvania Press, Philadelphia (1981) Google Scholar
  12. 12.
    Goldberg, J.A.: Interrupting the discourse on interruptions: An analysis in terms of relationally neutral, power-and rapport-oriented acts. J. Pragmat. 14(6), 883–903 (1990)CrossRefGoogle Scholar
  13. 13.
    Hall, E.T.: The Hidden Dimension, vol. 1990. Anchor Books, New York (1969) Google Scholar
  14. 14.
    Johnson, W.L., Marsella, S., Vilhjalmsson, H.: The darwars tactical language training system. In: Proceedings of I/ITSEC (2004)Google Scholar
  15. 15.
    Kendon, A.: Conducting interaction: Patterns of behavior in focused encounters, vol. 7. CUP Archive (1990)Google Scholar
  16. 16.
    Kosinski, R.J.: A literature review on reaction time. Clemson University 10 (2008)Google Scholar
  17. 17.
    Lee, J., Marsella, S.: Modeling side participants and bystanders: the importance of being a laugh track. In: Vilhjálmsson, H.H., Kopp, S., Marsella, S., Thórisson, K.R. (eds.) IVA 2011. LNCS, vol. 6895, pp. 240–247. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  18. 18.
    Leßmann, N., Kranstedt, A., Wachsmuth, I.: Towards a cognitively motivated processing of turn-taking signals for the embodied conversational agent max. In: Proceedings Workshop Embodied Conversational Agents: Balanced Perception and Action, pp. 57–64. IEEE Computer Society (2004)Google Scholar
  19. 19.
  20. 20.
    Mehrabian, A.: Significance of posture and position in the communication of attitude and status relationships. Psychol. Bull. 71(5), 359 (1969)CrossRefGoogle Scholar
  21. 21.
    O’Connell, D.C., Kowal, S., Kaltenbacher, E.: Turn-taking: a critical analysis of the research tradition. J. Psycholinguist. Rss. 19(6), 345–373 (1990)CrossRefGoogle Scholar
  22. 22.
    Pecune, F., Cafaro, A., Chollet, M., Philippe, P., Pelachaud, C.: Suggestions for extending saiba with the vib platform. In: Proceedings of the Workshop on Architectures and Standards for Intelligent Virtual Agents at IVA 2014 (2014)Google Scholar
  23. 23.
    Pedica, C., Vilhjálmsson, H.H., Lárusdóttir, M.: Avatars in conversation: the importance of simulating territorial behavior. In: Allbeck, J., Badler, N., Bickmore, T., Pelachaud, C., Safonova, A. (eds.) IVA 2010. LNCS, vol. 6356, pp. 336–342. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  24. 24.
    Prada, R., Paiva, A.: Believable groups of synthetic characters. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2005, pp. 37–43. ACM, New York, NY, USA (2005)Google Scholar
  25. 25.
    Raux, A., Eskenazi, M.: A finite-state turn-taking model for spoken dialog systems. In: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 629–637. Association for Computational Linguistics (2009)Google Scholar
  26. 26.
    Ravenet, B., Cafaro, A., Ochs, M., Pelachaud, C.: Interpersonal attitude of a speaking agent in simulated group conversations. In: Bickmore, T., Marsella, S., Sidner, C. (eds.) IVA 2014. LNCS, vol. 8637, pp. 345–349. Springer, Heidelberg (2014) Google Scholar
  27. 27.
    Ravenet, B., Ochs, M., Pelachaud, C.: From a user-created corpus of virtual agent’s non-verbal behavior to a computational model of interpersonal attitudes. In: Aylett, R., Krenn, B., Pelachaud, C., Shimodaira, H. (eds.) IVA 2013. LNCS, vol. 8108, pp. 263–274. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  28. 28.
    Rehm, M., Endrass, B.: Rapid prototyping of social group dynamics in multiagent systems. AI Soc. 24, 13–23 (2009)CrossRefGoogle Scholar
  29. 29.
    Reynolds, C.: Steering behaviors for autonomous characters. In: Proceedings of the Game Developers Conference, pp. 763–782. Miller Freeman Game Groups, San Francisco, CA (1999)Google Scholar
  30. 30.
    Sacks, H., Schegloff, E.A., Jefferson, G.: A simplest systematics for the organization of turn-taking for conversation. Language 50, 696–735 (1974)CrossRefGoogle Scholar
  31. 31.
    Sadler, P., Woody, E.: Interpersonal complementarity. Handbook of interpersonal psychology: Theory, research, assessment, and therapeutic interventions, p. 123 (2010)Google Scholar
  32. 32.
    Scheflen, A.E., Ashcraft, N.: Human Territories: How We Behave in Space-Time. Prentice-Hall, Englewood Cliffs (1976)Google Scholar
  33. 33.
    ter Maat, M., Truong, K.P., Heylen, D.: How turn-taking strategies influence users’ impressions of an agent. In: Allbeck, J., Badler, N., Bickmore, T., Pelachaud, C., Safonova, A. (eds.) IVA 2010. LNCS, vol. 6356, pp. 441–453. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  34. 34.
    Thórisson, K.R., Gislason, O., Jonsdottir, G.R., Thorisson, HTh: A multiparty multimodal architecture for realtime turntaking. In: Allbeck, J., Badler, N., Bickmore, T., Pelachaud, C., Safonova, A. (eds.) IVA 2010. LNCS, vol. 6356, pp. 350–356. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  35. 35.
    Vilhjálmsson, H.H.: Animating conversation in online games. In: Rauterberg, M. (ed.) ICEC 2004. LNCS, vol. 3166, pp. 139–150. Springer, Heidelberg (2004) CrossRefGoogle Scholar
  36. 36.
    Wiggins, J.S., Trapnell, P., Phillips, N.: Psychometric and geometric characteristics of the revised interpersonal adjective scales (IAS-R). Multivar. Behav. Res. 23(4), 517–530 (1988)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Brian Ravenet
    • 1
  • Angelo Cafaro
    • 2
  • Beatrice Biancardi
    • 2
  • Magalie Ochs
    • 3
  • Catherine Pelachaud
    • 2
  1. 1.Institut Mines-TélécomTélécom ParisTech, CNRS-LTCIParisFrance
  2. 2.Télécom ParisTech, CNRS-LTCIParisFrance
  3. 3.Aix Marseille Université, CNRS, ENSAM, Université de Toulon, LSIS UMR7296MarseilleFrance

Personalised recommendations