Interaction History in Adaptive Multimodal Interaction

  • Nikola Bubalo
  • Felix Schüssel
  • Frank Honold
  • Michael Weber
  • Anke Huckauf
Chapter
Part of the Cognitive Technologies book series (COGTECH)

Abstract

Modern Companion-Technologies provide multimodal and adaptive interaction possibilities. However, it is still unclear which user characteristics should be used in which manner to optimally support the interaction. An important aspect is that users themselves learn and adapt their behavior and preferences based on their own experiences. In other words, certain characteristics of user behavior are slowly but continuously changed and updated by the users themselves over multiple encounters with the Companion-Technology. Thus, a biological adaptive multimodal system observes and interacts with an electronic one, and vice versa. Consequently, such a user-centered interaction history is essential and should be integrated in the prediction of user behavior. Doing so enables the Companion to achieve more robust predictions of user behavior, which in turn leads to better fusion decisions and more efficient customization of the UI. We present the development of an experimental paradigm based on visual search tasks. The setup allows the induction of various user experiences as well as the testing of their effects on user behavior and preferences during multimodal interaction.

Notes

Acknowledgements

This work was done within the Transregional Collaborative Research Centre SFB/TRR 62 “Companion-Technology for Cognitive Technical Systems” funded by the German Research Foundation (DFG).

References

  1. 1.
    Ailomaa, M., Melichar, M., Rajman, M., Lisowska, A., Armstrong, S.: Archivus: a multimodal system for multimedia meeting browsing and retrieval. In: Proceedings of the COLING/ACL on Interactive Presentation Sessions, pp. 49–52. Association for Computational Linguistics, Stroudsburg, PA (2006)Google Scholar
  2. 2.
    Ajzen, I.: Attitudes, Personality, and Behavior. McGraw-Hill International, Maidenhead (2005)Google Scholar
  3. 3.
    Bellik, Y., Rebaï, I., Machrouh, E., Barzaj, Y., Jacquet, C., Pruvost, G., Sansonnet, J.P.: Multimodal interaction within ambient environments: an exploratory study. In: Human-Computer Interaction–INTERACT 2009, pp. 89–92. Springer, Berlin (2009)Google Scholar
  4. 4.
    Biundo, S., Wendemuth, A.: Companion-technology for cognitive technical systems. Künstl. Intell. 30(1), 71–75 (2016). Special issue on companion technologiesGoogle Scholar
  5. 5.
    Bolt, R.A.: “Put-That-There”: Voice and Gesture at the Graphics Interface, vol. 14. ACM, New York (1980)Google Scholar
  6. 6.
    Camp, G., Paas, F., Rikers, R., van Merrienboer, J.: Dynamic problem selection in air traffic control training: a comparison between performance, mental effort and mental efficiency. Comput. Hum. Behav. 17(5), 575–595 (2001)CrossRefGoogle Scholar
  7. 7.
    Carter, S., Mankoff, J., Klemmer, S.R., Matthews, T.: Exiting the cleanroom: on ecological validity and ubiquitous computing. Hum. Comput. Interact. 23(1), 47–99 (2008)CrossRefGoogle Scholar
  8. 8.
    Cohen, P.R., Johnston, M., McGee, D., Oviatt, S., Pittman, J., Smith, I., Chen, L., Clow, J.: Quickset: multimodal interaction for distributed applications. In: Proceedings of the Fifth ACM International Conference on Multimedia, pp. 31–40. ACM, New York (1997)Google Scholar
  9. 9.
    De Angeli, A., Gerbino, W., Cassano, G., Petrelli, D.: Visual display, pointing, and natural language: the power of multimodal interaction. In: Proceedings of the Working Conference on Advanced Visual Interfaces, pp. 164–173. ACM, New York (1998)Google Scholar
  10. 10.
    Dey, P., Madhvanath, S., Ranjan, A., Das, S.: An exploration of gesture-speech multimodal patterns for touch interfaces. In: Proceedings of the 3rd International Conference on Human Computer Interaction, pp. 79–83. ACM, New York (2011)Google Scholar
  11. 11.
    Domjan, M.: The principles of learning and behavior. Cengage Learning, Stamford, CT (2014)Google Scholar
  12. 12.
    Dumas, B., Lalanne, D., Oviatt, S.: Multimodal interfaces: a survey of principles, models and frameworks. In: Lalanne, D., Kohlas, J. (eds.) Human Machine Interaction. Lecture Notes in Computer Science, vol. 5440, pp. 3–26. Springer, Berlin, Heidelberg (2009)CrossRefGoogle Scholar
  13. 13.
    Haas, E.C., Pillalamarri, K.S., Stachowiak, C.C., McCullough, G.: Temporal binding of multimodal controls for dynamic map displays: a systems approach. In: Proceedings of the 13th International Conference on Multimodal Interfaces, pp. 409–416. ACM, New York (2011)Google Scholar
  14. 14.
    Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. Adv. Psychol. 52, 139–183 (1988)CrossRefGoogle Scholar
  15. 15.
    Hollender, N., Hofmann, C., Deneke, M., Schmitz, B.: Integrating cognitive load theory and concepts of human–computer interaction. Comput. Hum. Behav. 26(6), 1278–1288 (2010)CrossRefGoogle Scholar
  16. 16.
    Jaimes, A., Sebe, N.: Multimodal human–computer interaction: a survey. Comput. Vis. Image Underst. 108(1), 116–134 (2007)CrossRefGoogle Scholar
  17. 17.
    Jöst, M., Häußler, J., Merdes, M., Malaka, R.: Multimodal interaction for pedestrians: an evaluation study. In: Proceedings of the 10th International Conference on Intelligent User Interfaces, pp. 59–66. ACM, New York (2005)Google Scholar
  18. 18.
    Käster, T., Pfeiffer, M., Bauckhage, C.: Combining speech and haptics for intuitive and efficient navigation through image databases. In: Proceedings of the 5th International Conference on Multimodal Interfaces, pp. 180–187. ACM, New York (2003)Google Scholar
  19. 19.
    Kieffer, S., Carbonell, N.: How really effective are multimodal hints in enhancing visual target spotting? Some evidence from a usability study. J. Multimodal User Interfaces 1(1), 1–5 (2007)CrossRefGoogle Scholar
  20. 20.
    Koons, D.B., Sparrell, C.J., Thorisson, K.R.: Integrating Simultaneous Input from Speech, Gaze, and Hand Gestures. MIT, Menlo Park, CA, pp. 257–276 (1993)Google Scholar
  21. 21.
    Kruijff-Korbayová, I., Blaylock, N., Gerstenberger, C., Rieser, V., Becker, T., Kaisser, M., Poller, P., Schehl, J.: An experiment setup for collecting data for adaptive output planning in a multimodal dialogue system. In: Proceedings of ENLG (2005)Google Scholar
  22. 22.
    Lalanne, D., Nigay, L., Robinson, P., Vanderdonckt, J., Ladry, J.F., et al.: Fusion engines for multimodal input: a survey. In: Proceedings of the 2009 International Conference on Multimodal Interfaces, pp. 153–160. ACM, New York (2009)Google Scholar
  23. 23.
    Lee, M., Billinghurst, M.: A wizard of oz study for an ar multimodal interface. In: Proceedings of the 10th International Conference on Multimodal Interfaces, pp. 249–256. ACM, New York (2008)Google Scholar
  24. 24.
    Lee, J.H., Poliakoff, E., Spence, C.: The effect of multimodal feedback presented via a touch screen on the performance of older adults. In: Haptic and Audio Interaction Design, pp. 128–135. Springer, Berlin (2009)Google Scholar
  25. 25.
    Mignot, C., Valot, C., Carbonell, N.: An experimental study of future “natural” multimodal human-computer interaction. In: INTERACT’93 and CHI’93 Conference Companion on Human Factors in Computing Systems, pp. 67–68. ACM, New York (1993)Google Scholar
  26. 26.
    Müller, H.J., Krummenacher, J.: Visual search and selective attention. Vis. Cogn. 14(4–8), 389–410 (2006)CrossRefGoogle Scholar
  27. 27.
    Neal, J.G., Shapiro, S.C.: Intelligent multi-media interface technology. ACM SIGCHI Bull. 20(1), 75–76 (1988)CrossRefGoogle Scholar
  28. 28.
    Ouellette, J.A., Wood, W.: Habit and intention in everyday life: the multiple processes by which past behavior predicts future behavior. Psychol. Bull. 124(1), 54 (1998)CrossRefGoogle Scholar
  29. 29.
    Oviatt, S.: Multimodal interactive maps: designing for human performance. Hum. Comput. Interact. 12(1), 93–129 (1997)CrossRefGoogle Scholar
  30. 30.
    Oviatt, S., Cohen, P., Wu, L., Vergo, J., Duncan, L., Suhm, B., Bers, J., Holzman, T., Winograd, T., Landay, J., Larson, J., Ferro, D.: Designing the user interface for multimodal speech and pen-based gesture applications: state-of-the-art systems and future research directions. Hum. Comput. Interact. 15(4), 263–322 (2000)CrossRefGoogle Scholar
  31. 31.
    Oviatt, S., Coulston, R., Lunsford, R.: When do we interact multimodally?: Cognitive load and multimodal communication patterns. In: Proceedings of the 6th International Conference on Multimodal Interfaces, pp. 129–136. ACM, New York (2004)Google Scholar
  32. 32.
    Oviatt, S., Lunsford, R., Coulston, R.: Individual differences in multimodal integration patterns: what are they and why do they exist? In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 241–249. ACM, New York (2005)Google Scholar
  33. 33.
    Oviatt, S., Arthur, A., Cohen, J.: Quiet interfaces that help students think. In: Proceedings of the 19th Annual ACM Symposium on User Interface Software and Technology, pp. 191–200. ACM, New York (2006)Google Scholar
  34. 34.
    Paas, F., Tuovinen, J.E., Tabbers, H., Van Gerven, P.W.: Cognitive load measurement as a means to advance cognitive load theory. Educ. Psychol. 38(1), 63–71 (2003)CrossRefGoogle Scholar
  35. 35.
    Paivio, A.: Mental Representations: A Dual Coding Approach. Oxford University Press, Oxford (1990)CrossRefGoogle Scholar
  36. 36.
    Ratzka, A.: Explorative studies on multimodal interaction in a PDA- and desktop-based scenario. In: Proceedings of the 10th International Conference on Multimodal Interfaces, pp. 121–128. ACM, New York (2008)Google Scholar
  37. 37.
    Reeves, L.M., Lai, J., Larson, J.A., Oviatt, S., Balaji, T.S., Buisine, S., Collings, P., Cohen, P., Kraal, B., Martin, J.C., McTear, M., Raman, T., Stanney, K.M., Su, H., Wang, Q.Y.: Guidelines for multimodal user interface design. Commun. ACM 47(1), 57–59 (2004)CrossRefGoogle Scholar
  38. 38.
    Reis, T., de Sá, M., Carriço, L.: Multimodal interaction: real context studies on mobile digital artefacts. In: Haptic and Audio Interaction Design, pp. 60–69. Springer, Berlin (2008)Google Scholar
  39. 39.
    Ren, X., Zhang, G., Dai, G.: An experimental study of input modes for multimodal human-computer interaction. In: Advances in Multimodal Interfaces-ICMI 2000, pp. 49–56. Springer, Berlin (2000)Google Scholar
  40. 40.
    Ruiz, N., Chen, F., Oviatt, S.: Multimodal input. In: Multimodal Signal Processing: Theory and Applications for Human-Computer Interaction, p. 231. Academic, Boston (2009)Google Scholar
  41. 41.
    Savidis, A., Stephanidis, C.: Unified user interface design: designing universally accessible interactions. Interact. Comput. 16(2), 243–270 (2004)CrossRefGoogle Scholar
  42. 42.
    Schüssel, F., Honold, F., Weber, M.: Influencing factors on multimodal interaction during selection tasks. J. Multimodal User Interfaces 7(4), 299–310 (2013)CrossRefGoogle Scholar
  43. 43.
    Schüssel, F., Honold, F., Weber, M., Schmidt, M., Bubalo, N., Huckauf, A.: Multimodal interaction history and its use in error detection and recovery. In: Proceedings of the 16th ACM International Conference on Multimodal Interaction, ICMI ’14, pp. 164–171. ACM, New York (2014). doi:10.1145/2663204.2663255Google Scholar
  44. 44.
    Treisman, A.M., Gelade, G.: A feature-integration theory of attention. Cogn. Psychol. 12(1), 97–136 (1980)CrossRefGoogle Scholar
  45. 45.
    Van Merrienboer, J.J., Sweller, J.: Cognitive load theory and complex learning: recent developments and future directions. Educ. Psychol. Rev. 17(2), 147–177 (2005)CrossRefGoogle Scholar
  46. 46.
    Wasinger, R., Krüger, A.: Modality preferences in mobile and instrumented environments. In: Proceedings of the 11th International Conference on Intelligent User Interfaces, pp. 336–338. ACM, New York (2006)Google Scholar
  47. 47.
    Wickens, C.D.: Multiple resources and mental workload. Hum. Factors J. Hum. Factors Ergon. Soc. 50(3), 449–455 (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Nikola Bubalo
    • 1
  • Felix Schüssel
    • 2
  • Frank Honold
    • 2
  • Michael Weber
    • 2
  • Anke Huckauf
    • 1
  1. 1.General PsychologyUniversity UlmUlmGermany
  2. 2.Institute for Media InformaticsUniversity UlmUlmGermany

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