Study of Face-to-Face Dyadic Conversation Behavior on Uneven Meal Distribution Setting for Designing an Attentive Listening Agent

  • Hiromi Hanawa
  • Tomoo Inoue
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 460)

Abstract

A conversation over a meal and its support as a research topic has been gaining attention. Although all the researches so far assumed all participants have a meal, this paper points out the uneven meal distribution setting as an additional case to analyze. After conducting a face-to-face dyadic conversation experiment, analyses show that uneven meal distribution induces the narrator-active listener structure in dyadic conversation at a table. Accordingly the setting elicits attentive listening communication and proposed design of attentive listening agents.

Keywords

Attentive Listening Dyadic Interaction Listening Agent Conversation over meal Communication Aid Dialogue Dining Table Table Talk Face-to-face 

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References

  1. 1.
    Mukawa, N.: Analysis and Application of Dining Communication: Development system to share enjoyment of eating. Journal of Information Processing Society of Japan 52(11), 1397–1402 (2011) (in Japanese)Google Scholar
  2. 2.
    Grimes, A., Harper, R.: Celebratory technology: New directions for food research in HCI. In: Proceedings of the ACM-CHI Conference on Human Factors in Computing Systems 2008, pp. 467–476 (2008)Google Scholar
  3. 3.
    Comber, R., Ganglbauer, E., Choi, J.H.-J., Hoonhout, J., Rogers, V., O’Hara, K., Maitland, J.: Food and interaction design: designing for food in everyday life. In: Proceedings of the 12th ACM-SIGCHI Conference on Human Factors in Computing Systems, pp. 2767–2770 (2012)Google Scholar
  4. 4.
    Seto, Y., Noguchi, Tosaka, M., Inoue, T.: Development of an another dish re-commender based on dining activity recognition, Technical Report. The Institute of Electronics, Information and Communication Engineers 107(554), 55–60 (2008)Google Scholar
  5. 5.
    Narumi, T., Ban, Y., Kajinami, T., Tanikawa, T., Hirose, M.: Augmented perception of satiety: controlling food consumption by changing apparent size of food with augmented reality. In: Proceedings of the ACM-CHI Conference on Human Factors in Computing Systems, pp. 109–118 (2012)Google Scholar
  6. 6.
    Mukawa, N., Tokunaga, H., Yuasa, M., Tsuda, Y., Tateyama, K., Kasamatsu, C.: Analysis on Utterance Behaviors Embedded in Eating Actions: How are Conversations and Hand-Mouth-Motions Controlled in Three-Party Table Talk? The Institute of Electronics, Information and Communication Engineers (A) J94-A(7), 500–508 (2011)Google Scholar
  7. 7.
    Inoue, T., Otake, M.: Effect of meal in triadic table talk: Equalization of speech and gesture between participants. Transactions of Human Interface Society 13(3), 19–29 (2011)Google Scholar
  8. 8.
    Furukawa, D., Inoue, T.: Showing meal in video-mediated table talk makes conversation close to face-to-face. Journal of Information Processing Society of Japan 54(1), 266–274 (2013)Google Scholar
  9. 9.
    Nawahdah, M., Inoue, T.: Virtually dining together in time-shifted environment: KIZUNA design. In: Proceedings of the 13th ACM Conference on Computer-Supported Cooperative Work, pp. 779–788 (2013)Google Scholar
  10. 10.
    Higaki, Y., Furukawa, D., Inoue, T.: Difference in face-to-face dyadic conversation behavior on uneven meal distribution settings. Technical Report, The Institute of Electronics, Information and Communication Engineers 113(72), 91–96 (2013)Google Scholar
  11. 11.
    Enomoto, M., Ishizaki, M., Koiso, H., Den, Y., Mizukami, E., Yano, H.: A Statistical Investigation of Basic Units for Spoken Interaction Analysis, Technical Report. The Institute of Electronics, Information and Communication Engineers 104(445), 45–50 (2004) (in Japanese)Google Scholar
  12. 12.
    Mizukami, E., Yano, H.: The Structure of Inter-Pausal Unit in Dialogue, Technical Report. The Japanese Society for Artificial Intelligence, Special Interest Group on Spoken Language Understanding and Dialogue Processing 39, 43–48 (2003)Google Scholar
  13. 13.
    Weizenbaum, J.: ELIZA: A computer program for the study of natural language communication between man and machine. Communications of the ACM 9(1), 36–45 (1966)CrossRefGoogle Scholar
  14. 14.
    Reeves, E., Nass, C.: The media equation: How people treat computers, television, and new media like real people and places. The Center for the Study of Language and Information Publications (1996)Google Scholar
  15. 15.
    Shibusawa, S., Huang, H., Hayashi, Y., Kawagoe, K.: An Empirical Analysis on the Relationship of Mood and Attitude between Talkers during Active Listening: Toward Active Listening Agent for the Elderly, Technical Report. The Institute of Electronics, Information and Communication Engineers, Human Communication Society 2012-75, 125–129 (2013) (in Japanese)Google Scholar
  16. 16.
    Wada, K., Shibata, T.: Living with seal robots: Its socio-psychological and physiological influences on the elderly in a care house. IEEE Transactions on Robotics and Mechatronics 19(6), 691–697 (2007)Google Scholar
  17. 17.
    Kobayashi, Y., et al.: Design targeting voice interface robot capable of active listening. In: Proceedings of the 5th ACM/IEEE International Conference on Human-robot Interaction, pp. 161–162 (2010)Google Scholar
  18. 18.
    Watanabe, T., et al.: InterActor: Speech-Driven Embodied Interactive Actor. International Journal of Human - Computer Interaction 17(1), 43–60 (2004)CrossRefGoogle Scholar
  19. 19.
    Richardson, J.T.E.: Handbook of qualitative research methods for psychology and the social sciences. Wiley-Blackwell (April 1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Hiromi Hanawa
    • 1
  • Tomoo Inoue
    • 1
  1. 1.Graduate School of Library, Information and Media StudiesUniversity of TsukubaTsukubaJapan

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