Advertisement

Detecting Microstructures of Conversations by Using Physical References: Case Study of Poster Presentations

  • Ken Kumagai
  • Yasuyuki Sumi
  • Kenji Mase
  • Toyoaki Nishida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4012)

Abstract

The purpose of the work presented in this paper is reusing conversational archives for supporting knowledge circulation in the real world. So far, we have proposed a method to give structures to conversations by analyzing gaze and utterance data from an interaction corpus, which is a semi-structured set of a large amount of interaction data collected by various sensors. In this paper, we give more detailed structures to conversations by analyzing poster touch data. We devise a poster touch capturing method and investigate the correlation between poster touch and conversation structure, that is, a topic of conversation has a relation to a sub-theme in a poster that an exhibitor touched at the time when it was made. By analyzing the relation between conversations and poster touch data, we can detect the transition of topics and divide a long conversation that is composed of many topics into some microstructured conversations that are composed of a single topic or context.

Keywords

Tree Model Contextual Data Head Direction Deictic Gesture Physical Reference 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Nishida, T.: Conversation quantization for conversational knowledge process. In: Bhalla, S. (ed.) DNIS 2005. LNCS, vol. 3433, pp. 15–33. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Chiu, P., Kapuskar, A., Reitmeier, S., Wilcox, L.: Meeting capture in a media enriched conference room. In: Streitz, N.A., Hartkopf, V. (eds.) CoBuild 1999. LNCS, vol. 1670, pp. 79–88. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  3. 3.
    Minoh, M.: Automatic lecture archiving system. In: Proceedings of the 12th International Conference on Informatics Research for Development of Knowledge Society Infrastructure (ICKS 2004) (2004)Google Scholar
  4. 4.
    Ito, S., Sumi, Y., Mase, K., Kunifuji, S.: SmartCourier: Annotation management tool for research labs. In: Proceedings of the Sixth International Conference on Knowledge-based Intelligent Information Engineering Systems and Allied Technologies (KES 2002), September 2002, pp. 827–832. IOS Press, Amsterdam (2002)Google Scholar
  5. 5.
    Otsuka, K., Takemae, Y., Yamato, J., Murase, H.: Probabilistic inference of gaze patterns and structure of multiparty conversations from head directions and utterances. In: Washio, T., Sakurai, A., Nakajima, K., Takeda, H., Tojo, S., Yokoo, M. (eds.) JSAI Workshop 2006. LNCS, vol. 4012, pp. 353–364. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    McNeill, D.: Hand and Mind: What Gestures Reveal about Thought. U. of Chicago Press (1992)Google Scholar
  7. 7.
    Sumi, Y., Ito, S., Matsuguchi, T., Fels, S., Mase, K.: Collaborative capturing and interpretation of interactions. In: Pervasive 2004 Workshop on Memory and Sharing of Experiences, pp. 1–7 (2004), http://www.ii.ist.i.kyoto-u.ac.jp/~sumi/pervasive04/
  8. 8.
    Kawaguchi, Y., Sumi, Y., Nishida, T., Mase, K.: Presentation agents by reusing past conversational data in exhibition sites. IPSJ SIG Technical Reports 2005(28), 225–232, (in Japanese) (2005) Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ken Kumagai
    • 1
    • 2
  • Yasuyuki Sumi
    • 1
    • 2
  • Kenji Mase
    • 2
    • 3
  • Toyoaki Nishida
    • 1
    • 2
  1. 1.Graduate School of InformaticsKyoto UniversityKyotoJapan
  2. 2.ATR Media Information Science LaboratoriesKyotoJapan
  3. 3.Information Technology CenterNagoya UniversityChikusaJapan

Personalised recommendations