Skip to main content

Gaze-X: Adaptive, Affective, Multimodal Interface for Single-User Office Scenarios

  • Conference paper
Artifical Intelligence for Human Computing

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4451))

Abstract

This paper describes an intelligent system that we developed to support affective multimodal human-computer interaction (AMM-HCI) where the user’s actions and emotions are modeled and then used to adapt the interaction and support the user in his or her activity. The proposed system, which we named Gaze-X, is based on sensing and interpretation of the human part of the computer’s context, known as W5+ (who, where, what, when, why, how). It integrates a number of natural human communicative modalities including speech, eye gaze direction, face and facial expression, and a number of standard HCI modalities like keystrokes, mouse movements, and active software identification, which, in turn, are fed into processes that provide decision making and adapt the HCI to support the user in his or her activity according to his or her preferences. A usability study conducted in an office scenario with a number of users indicates that Gaze-X is perceived as effective, easy to use, useful, and affectively qualitative.

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. Bartsch-Sporl, B., Lez, M., Hubner, A.: Case-based reasoning – survey and future directions. In: Puppe, F. (ed.) XPS 1999. LNCS (LNAI), vol. 1570, pp. 67–89. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  2. Bianchi-Berthouze, N., Lisetti, C.L.: Modeling multimodal expression of user’s affective subjective experience. User Modeling and User-Adapted Interaction 12(1), 49–84 (2002)

    Article  MATH  Google Scholar 

  3. Bolt, R.A.: Put-that-there: Voice and gesture at the graphics interface. Computer Graphics (Proc. ACM SIGGRAPH’80) 14(3), 262–270 (1980)

    Article  MathSciNet  Google Scholar 

  4. Browne, D., Norman, M., Riches, D.: Why Build Adaptive Interfaces? In: Browne, D., Totterdell, P., Norman, M. (eds.) Adaptive User Interfaces, pp. 15–57. Academic Press, London (1990)

    Google Scholar 

  5. Caridakis, G., et al.: Modeling Naturalistic Affective States via Facial and Vocal Expressions Recognition. In: Proc. Int’l Conf. Multimodal Interfaces, pp. 146–154 (2006)

    Google Scholar 

  6. Cohen, P., Oviatt, S.L.: The role of voice input for human-machine communication. Proc. National Academy of Sciences 92, 9921–9927 (1995)

    Article  Google Scholar 

  7. Conati, C.: Probabilistic assessment of user’s emotions in educational games. Applied Artificial Intelligence 16(7-8), 555–575 (2002)

    Article  Google Scholar 

  8. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Trans. Pattern Analysis and Machine Intelligence 23(6), 681–685 (2001)

    Article  Google Scholar 

  9. Deng, B.L., Huang, X.: Challenges in adopting speech recognition. Communications of the ACM 47(1), 69–75 (2004)

    Article  Google Scholar 

  10. Dey, A.K., Abowd, G.D., Salber, D.: A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. J. Human-Computer Interaction 16(2-4), 97–166 (2001)

    Article  Google Scholar 

  11. Duric, Z., et al.: Integrating perceptual and cognitive modeling for adaptive and intelligent human-computer interaction. Proceedings of the IEEE 90(7), 1272–1289 (2002)

    Article  Google Scholar 

  12. El Kaliouby, R., Robinson, P.: Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures. Proc. Int’l Conf. Computer Vision & Pattern Recognition 3, 154 (2004)

    Google Scholar 

  13. Gu, H., Ji, Q.: An automated face reader for fatigue detection. In: Proc. Int’l Conf. Face & Gesture Recognition, pp. 111–116 (2006)

    Google Scholar 

  14. Gunes, H., Piccardi, M.: Affect Recognition from Face and Body: Early Fusion vs. Late Fusion. In: Proc. Int’l Conf. Systems, Man and Cybernetics, pp. 3437–3443 (2005)

    Google Scholar 

  15. Hauptmann, A.G.: Speech and gestures for graphic image manipulation. In: Proc. ACM Int’l Conf. Human Factors in Computing Systems, pp. 241–245 (1989)

    Google Scholar 

  16. Hoffman, D.L., Novak, T.P., Venkatesh, A.: Has the Internet become indispensable? Communications of the ACM 47(7), 37–42 (2004)

    Article  Google Scholar 

  17. Hudlicka, E.: To feel or not to feel: The role of affect in human-computer interaction. Int’l J. Human-Computer Studies 59(1-2), 1–32 (2003)

    Article  Google Scholar 

  18. Hudlicka, E., McNeese, M.D.: Assessment of user affective/belief states for interface adaptation. User Modeling & User-Adapted Interaction 12(1), 1–47 (2002)

    Article  MATH  Google Scholar 

  19. Jaimes, A., Sebe, N.: Multimodal human computer interaction: A survey. In: Proc. IEEE ICCV Int’l Workshop on HCI in conjunction with Int’l Conf. Computer Vision (2005)

    Google Scholar 

  20. Kapoor, A., Picard, R.W.: Multimodal affect recognition in learning environments. In: Proc. ACM Int’l Conf. Multimedia, pp. 677–682 (2005)

    Google Scholar 

  21. Keltner, D., Ekman, P.: Facial expression of emotion. In: Lewis, M., Haviland-Jones, J.M. (eds.) Handbook of Emotions, pp. 236–249. The Guilford Press, New York (2000)

    Google Scholar 

  22. van Kuilenburg, H., Wiering, M., den Uyl, M.: A model-based method for automatic facial expression recognition. In: Gama, J., et al. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 194–205. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  23. Lisetti, C.L., Nasoz, F.: MAUI: A multimodal affective user interface. In: Proc. Int’l Conf. Multimedia, pp. 161–170 (2002)

    Google Scholar 

  24. Lisetti, C.L., Schiano, D.J.: Automatic facial expression interpretation: Where human-computer interaction, AI and cognitive science intersect. Pragmatics and Cognition 8(1), 185–235 (2000)

    Article  Google Scholar 

  25. Maat, L., Pantic, M.: Gaze-X: Adaptive affective multimodal interface for single-user office scenarios. In: Proc. Int’l Conf. Multimodal Interfaces, pp. 171–178 (2006)

    Google Scholar 

  26. Maglio, P.P., et al.: SUITOR: An attentive information system. In: Proc. Int’l Conf. Intelligent User Interfaces, pp. 169–176 (2000)

    Google Scholar 

  27. Marsic, I., Medl, A., Flanagan, J.: Natural communication with information systems. Proceedings of the IEEE 88(8), 1354–1366 (2000)

    Article  Google Scholar 

  28. Nielsen, J.: Multimedia and hypertext: The Internet and beyond. Academic Press, Cambridge (1995)

    Google Scholar 

  29. Nock, H.J., Iyengar, G., Neti, C.: Multimodal processing by finding common cause. Communications of the ACM 47(1), 51–56 (2004)

    Article  Google Scholar 

  30. Oviatt, S.: User-centred modelling and evaluation of multimodal interfaces. Proceedings of the IEEE 91(9), 1457–1468 (2003)

    Article  Google Scholar 

  31. Oviatt, S., Darrell, T., Flickner, M.: Multimodal Interfaces that Flex, Adapt, and Persist. Communications of the ACM 47(1), 30–33 (2004)

    Article  Google Scholar 

  32. Pantic, M., Grootjans, R.J., Zwitserloot, R.: Teaching Ad-hoc Networks using a Simple Agent Framework. In: Proc. Int’l Conf. Information Technology Based Higher Education and Training, pp. 6–11 (2005)

    Google Scholar 

  33. Pantic, M., et al.: Human computing and machine understanding of human behaviour: A survey. In: Proc. Int’l Conf. Multimodal Interfaces, pp. 239–248 (2006)

    Google Scholar 

  34. Pantic, M., Rothkrantz, L.J.M.: Toward an affect-sensitive multimodal human-computer interaction. Proceedings of the IEEE 91(9), 1370–1390 (2003)

    Article  Google Scholar 

  35. Pantic, M., Rothkrantz, L.J.M.: Case-based reasoning for user-profiled recognition of emotions from face images. In: Proc. Int’l Conf. Multimedia and Expo, pp. 391–394 (2004)

    Google Scholar 

  36. Pantic, M., et al.: Affective multimodal human-computer interaction. In: Proc. ACM Int’l Conf. Multimedia, pp. 669–676 (2005)

    Google Scholar 

  37. Pentland, A.: Looking at people: Sensing for ubiquitous and wearable computing. IEEE Trans. Pattern Analysis and Machine Intelligence 22(1), 107–119 (2000)

    Article  Google Scholar 

  38. Pentland, A.: Perceptual intelligence. Communications of the ACM 43(3), 35–44 (2000)

    Article  Google Scholar 

  39. Picard, R.W.: Affective Computing. The MIT Press, Cambridge (1997)

    Google Scholar 

  40. Porta, M.: Vision-based user interfaces: methods and applications. Int’l J. Human-Computer Studies 57(1), 27–73 (2002)

    Article  Google Scholar 

  41. Preece, J., Schneiderman, B.: Survival of the fittest: Evolution of multimedia user interfaces. ACM Computing Surveys 27(4), 557–559 (1995)

    Article  Google Scholar 

  42. Prendinger, H., Ishizuka, M.: The empathic companion: A character-based interface that addresses users’ affective states. Applied Artificial Intelligence 19(3-4), 267–285 (2005)

    Article  Google Scholar 

  43. Reeves, L.M., et al.: Guidelines for multimodal user interface design. Communications of the ACM 47(1), 57–59 (2004)

    Article  Google Scholar 

  44. Ruttkay, Z., Pelachaud, C. (eds.): From brows to trust: Evaluating embodied conversational agents. Kluwer Academic Publishers, Norwell (2004)

    MATH  Google Scholar 

  45. Schank, R.C.: Memory based expert systems. AFOSR.TR. 84-0814, Comp. Science Dept., Yale University (1984)

    Google Scholar 

  46. Sharma, R., et al.: Speech-gesture driven multimodal interfaces for crisis management. Proceedings of the IEEE 91(9), 1327–1354 (2003)

    Article  Google Scholar 

  47. Sharp, H., Rogers, Y., Preece, J.: Interaction Design, 2nd edn. John Wiley & Sons, Chichester (2007)

    Google Scholar 

  48. Shneiderman, B.: Universal usability. Communications of the ACM 43(5), 85–91 (2000)

    Article  Google Scholar 

  49. Shneiderman, B.: CUU: Bridging the Digital Divide with Universal Usability. ACM Interactions 8(2), 11–15 (2001)

    Article  Google Scholar 

  50. Shoham, Y.: What we talk about when we talk about software agents. IEEE Intelligent Systems and Their Applications 14(2), 28–31 (1999)

    Article  Google Scholar 

  51. Tennenhouse, D.: Proactive computing. Communications of the ACM 43(5), 43–50 (2000)

    Article  Google Scholar 

  52. Turk, M.: Computer vision in the interface. Communications of the ACM 47(1), 61–67 (2004)

    Article  Google Scholar 

  53. Vo, M.T., Waibel, A.: Multimodal human-computer interaction. In: Proc. Int’l Symposium on Spoken Dialogue (1993)

    Google Scholar 

  54. Waibel, A., et al.: Multimodal Interfaces. Artificial Intelligence Review 10(3-4), 299–319 (1995)

    Article  Google Scholar 

  55. Zeng, Z., et al.: Audio-Visual Emotion Recognition in Adult Attachment Interview. In: Proc. Int’l Conf. Multimodal Interfaces, pp. 139–145 (2006)

    Google Scholar 

  56. Zhang, P., Li, N.: The importance of affective quality. Communications of the ACM 48(9), 105–108 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Thomas S. Huang Anton Nijholt Maja Pantic Alex Pentland

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Maat, L., Pantic, M. (2007). Gaze-X: Adaptive, Affective, Multimodal Interface for Single-User Office Scenarios. In: Huang, T.S., Nijholt, A., Pantic, M., Pentland, A. (eds) Artifical Intelligence for Human Computing. Lecture Notes in Computer Science(), vol 4451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72348-6_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72348-6_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72346-2

  • Online ISBN: 978-3-540-72348-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics