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Strangers and Friends

Adapting the Conversational Style of an Artificial Agent
  • Nikita Mattar
  • Ipke Wachsmuth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8008)

Abstract

We demonstrate how an artificial agent’s conversational style can be adapted to different interlocutors by using a model of Person Memory. While other approaches so far rely on adapting an agent’s behavior according to one particular factor like personality or relationship, we show how to enable an agent to take diverse factors into account at once by exploiting social categories. This way, our agent is able to adapt its conversational style individually to reflect interpersonal relationships during conversation.

Keywords

embodied conversational agents conversational style social categories personality relationships situational context 

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References

  1. 1.
    Bickmore, T., Cassell, J.: Relational Agents: A Model and Implementation of Building User Trust. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2001, pp. 396–403. ACM, New York (2001)Google Scholar
  2. 2.
    Bickmore, T., Schulman, D.: Empirical Validation of an Accommodation Theory-Based Model of User-Agent Relationship. In: Nakano, Y., Neff, M., Paiva, A., Walker, M. (eds.) IVA 2012. LNCS, vol. 7502, pp. 390–403. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Bickmore, T.W.: Relational Agents: Effecting Change through Human-Computer Relationships. Ph.D. thesis. Massachusetts Institute of Technology (2003)Google Scholar
  4. 4.
    Bickmore, T.W., Picard, R.W.: Establishing and Maintaining Long-Term Human-Computer Relationships. ACM Transactions on Computer-Human Interaction (ToCHI) 12(2), 293–327 (2005)CrossRefGoogle Scholar
  5. 5.
    Breuing, A., Wachsmuth, I.: Let’s Talk Topically with Artificial Agents! Providing Agents with Humanlike Topic Awareness in Everyday Dialog Situations. In: ICAART 2012 - Proceedings of the 4th International Conference on Agents and Artificial Intelligence, pp. 62–71. SciTePress (2012)Google Scholar
  6. 6.
    Eggins, S., Slade, D.: Analysing Casual Conversation. Cassell (1997)Google Scholar
  7. 7.
    Gulz, A., Haake, M., Silvervarg, A., Sjödén, B., Veletsianos, G.: Building a Social Conversational Pedagogical Agent: Design Challenges and Methodological approaches. In: Perez-Marin, D., Pascual-Nieto, I. (eds.) Conversational Agents and Natural Language Interaction: Techniques and Effective Practices, ch. 6, pp. 128–155. IGI Global (2011)Google Scholar
  8. 8.
    Kasap, Z., Ben Moussa, M., Chaudhuri, P., Magnenat-Thalmann, N.: Making Them Remember–Emotional Virtual Characters with Memory. IEEE Computer Graphics and Applications 29(2), 20–29 (2009)CrossRefGoogle Scholar
  9. 9.
    Kopp, S., Gesellensetter, L., Krämer, N.C., Wachsmuth, I.: A Conversational Agent as Museum Guide – Design and Evaluation of a Real-World Application. In: Panayiotopoulos, T., Gratch, J., Aylett, R.S., Ballin, D., Olivier, P., Rist, T. (eds.) IVA 2005. LNCS (LNAI), vol. 3661, pp. 329–343. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Mairesse, F.: Learning to Adapt in Dialogue Systems: Data-driven Models for Personality Recognition and Generation. Ph.D. thesis, University of Sheffield, Department of Computer Science (2008)Google Scholar
  11. 11.
    Mairesse, F., Walker, M.A.: Towards Personality-Based User Adaptation: Psychologically Informed Stylistic Language Generation. User Modeling and User-Adapted Interaction 20, 227–278 (2010)CrossRefGoogle Scholar
  12. 12.
    Mattar, N., Wachsmuth, I.: Small Talk Is More than Chit-Chat. In: Glimm, B., Krüger, A. (eds.) KI 2012. LNCS, vol. 7526, pp. 119–130. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Mattar, N., Wachsmuth, I.: Who Are You? On the Acquisition of Information about People for an Agent that Remembers. In: ICAART 2012 - Proceedings of the 4th International Conference on Agents and Artificial Intelligence, pp. 98–105. SciTePress (2012)Google Scholar
  14. 14.
    Reis, H.T., Capobianco, A., Tsai, F.F.: Finding the Person in Personal Relationships. Journal of Personality 70(6), 813–850 (2002)CrossRefGoogle Scholar
  15. 15.
    Selfhout, M., Burk, W., Branje, S., Denissen, J., van Aken, M., Meeus, W.: Emerging Late Adolescent Friendship Networks and Big Five Personality Traits: A Social Network Approach. Journal of Personality 78(2), 509–538 (2010)CrossRefGoogle Scholar
  16. 16.
    Svennevig, J.: Getting Acquainted in Conversation: A Study of Initial Interactions. Pragmatics & Beyond. John Benjamins Publishing Company (1999)Google Scholar
  17. 17.
    Tannen, D.: Conversational Style: Analyzing Talk among Friends. Oxford University Press, Oxford (2005)Google Scholar
  18. 18.
    Ventola, E.: The structure of casual conversation in english. Journal of Pragmatics 3(3-4), 267–298 (1979)CrossRefGoogle Scholar
  19. 19.
    Wahlster, W., Kobsa, A.: User models in dialog systems. In: Kobsa, A., Wahlster, W. (eds.) User Models in Dialog Systems, pp. 4–34. Springer, Berlin (1989)CrossRefGoogle Scholar
  20. 20.
    Wilks, Y.: Artificial Companions as a new kind of interface to the future Internet. Research Report 13, Oxford Internet Institute/University of Sheffield (2006)Google Scholar
  21. 21.
    Zayas, V., Shoda, Y., Ayduk, O.N.: Personality in Context: An Interpersonal Systems Perspective. Journal of Personality 70(6), 851–900 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nikita Mattar
    • 1
  • Ipke Wachsmuth
    • 1
  1. 1.Artificial Intelligence GroupBielefeld UniversityBielefeldGermany

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