Skip to main content

Modeling Behavioral Manifestations of Coordination and Rapport over Multiple Conversations

Speaking Rate as a Relational Indicator for a Virtual Agent

  • Conference paper
Book cover Intelligent Virtual Agents (IVA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6356))

Included in the following conference series:

Abstract

Many potential applications of virtual agents require an agent to conduct multiple conversations with users. An effective and engaging agent should modify its behavior in realistic ways over these conversations. To model these changes, we gathered a longitudinal video corpus of human-human counseling conversations, and constructed a model of changes in articulation rates over multiple conversations. Articulation rates are observed to increase over time, both within a single conversation and across conversations. However, articulation rates increased mainly for words spoken separately from larger phrases. We also present a preliminary evaluation study, showing that implementing such changes in a virtual agent has a measurable effect on user attitudes toward the agent.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cassell, J.: Embodied conversational agents. MIT Press, Cambridge (2000)

    Book  Google Scholar 

  2. 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, pp. 75–110. Oxford University Press, New York (2003)

    Chapter  Google Scholar 

  3. Cassell, J., Gill, A.J., Tepper, P.A.: Coordination in conversation and rapport. In: Workshop on Embodied Language Processing, Association for Computational Linguistics, pp. 41–50 (2007)

    Google Scholar 

  4. Smith, B.L., Brown, B.L., Strong, W.J., Rencher, A.C.: Effects of speech rate on personality perception. Language and Speech 18(2), 145–152 (1975)

    Article  Google Scholar 

  5. Nass, C., Lee, K.M.: Does computer-generated speech manifest personality? an experimental test of similarity-attraction. In: CHI 2000: Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 329–336. ACM, New York (2000)

    Google Scholar 

  6. Planalp, S., Benson, A.: Friends’ and acquaintances’ conversations I: Perceived differences. Journal of Social and Personal Relationships 9(4), 483–506 (1992)

    Article  Google Scholar 

  7. Yuan, J., Liberman, M., Cieri, C.: Towards an integrated understanding of speaking rate in conversation. In: International Conference on Spoken Language Processing, INTERSPEECH-2006 (2006)

    Google Scholar 

  8. Bickmore, T.: Relational agents: Effecting change through human-computer relationships (2003)

    Google Scholar 

  9. Horvath, A.O., Symonds, D.B.: Relation between working alliance and outcome in psychotherapy: A meta-analysis. Journal of Counseling Psychology 38(2), 139–149 (1991)

    Article  Google Scholar 

  10. Verbeke, G., Molenberghs, G.: Linear Mixed Models for Longitudinal Data. Springer, Heidelberg (2001)

    MATH  Google Scholar 

  11. Hadfield, J.: MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software 33(2), 1–22 (2009)

    Google Scholar 

  12. Quené, H.: Multilevel modeling of between-speaker and within-speaker variation in spontaneous speech tempo. The Journal of the Acoustical Society of America 123(2), 1104–1113 (2008)

    Article  Google Scholar 

  13. Nakatani, L.H., O’Connor, K.D., Aston, C.H.: Prosodic aspects of american english speech rhythm. The Journal of the Acoustical Society of America 69(S1), 82 (1981)

    Article  Google Scholar 

  14. Dahlbäck, N., Jönsson, A., Ahrenberg, L.: Wizard of oz studies: why and how. In: IUI 1993: Proceedings of the 1st international conference on Intelligent user interfaces, pp. 193–200. ACM, New York (1993)

    Google Scholar 

  15. Horvath, A.O., Greenberg, L.S.: Development and validation of the working alliance inventory. Journal of Counseling Psychology 36(2), 223–233 (1989)

    Article  Google Scholar 

  16. Wiggins, J.S.: A psychological taxonomy of trait-descriptive terms: The interpersonal domain. Journal of Personality and Social Psychology 37(3), 395–412 (1979)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schulman, D., Bickmore, T. (2010). Modeling Behavioral Manifestations of Coordination and Rapport over Multiple Conversations. In: Allbeck, J., Badler, N., Bickmore, T., Pelachaud, C., Safonova, A. (eds) Intelligent Virtual Agents. IVA 2010. Lecture Notes in Computer Science(), vol 6356. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15892-6_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15892-6_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15891-9

  • Online ISBN: 978-3-642-15892-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics