Estimation of Interruptibility during Office Work Based on PC Activity and Conversation

  • Satoshi Hashimoto
  • Takahiro Tanaka
  • Kazuaki Aoki
  • Kinya Fujita
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8018)

Abstract

The chances of being interrupted by online communication systems, such as email, instant messenger, and micro-blog, are rapidly increasing. For the adequate control of interruption timing, the real-time estimation of the interruptibility of the user is required. In this study, we propose an interruptibility estimation method using PC activity and conversational voice detection based on the wavelet transform. The offline estimation was applied to a dataset of 50 hours obtained from 10 users. The results indicated the feasibility of improving the interruptibility estimation accuracy by the automatic detection of the existence and end of conversations.

Keywords

interruptibility availability voice detection office work interruption 

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References

  1. 1.
    Altman, E.M., Trafton, J.G.: Memory for Goals: An Activation-based Model. Cog. Sci. 26, 39–83 (2002)CrossRefGoogle Scholar
  2. 2.
    Salvucci, D.D., Taatgen, N.A.: Threaded Cognition: An Integrated Theory of Concurrent Multitasking. Psychol. Rev. 115(1), 101–130 (2008)CrossRefGoogle Scholar
  3. 3.
    Cutrell, E.B., Czerwinski, M., Horvitz, E.: Effects of instant messaging interruptions on computing tasks. In: Extended Abstracts on Human Factors in Computing Systems, pp. 99–100 (2000)Google Scholar
  4. 4.
    Monk, C.A., Trafton, J.G., Boehm-Davis, D.A.: The Effect of Interruption Duration and Demand on Resuming Suspended Goals. J. Exp. Psychol. Appl. 14, 299–313 (2008)CrossRefGoogle Scholar
  5. 5.
    Mark, G., Gonzalez, V.M., Harris, J.: No Task Left Behind? Examining the Nature of Fragmented Work. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 321–330. ACM, New York (2005)Google Scholar
  6. 6.
    Honda, S., Tomioka, H., Kimura, T., Oosawa, T., Okada, K., Matsushita, Y.: A Home Office Environment based on the Concentration Degrees of Workers: A Virtual Office System Valentine. Trans. Inform. Process. Soc. Jpn. 39(5), 1472–1483 (1998) (in Japanese) Google Scholar
  7. 7.
    Avrahami, D., Fogarty, J., Hudson, S.E.: Biases in Human Estimation of Interruptibility: Effects and Implications for Practice. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 50–60. ACM, New York (2007)CrossRefGoogle Scholar
  8. 8.
    Fogarty, J., Hudson, S.E.: Toolkit Support for Developing and Deploying Sensor-based Statistical Models of Human Situations. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 135–144. ACM, New York (2007)CrossRefGoogle Scholar
  9. 9.
    Danninger, M., Stiefelhagen, R.: A Context-Aware Virtual Secretary in a Smart Office Environment. In: Proceedings of the 16th ACM International Conference on Multimedia, pp. 529–538. ACM, New York (2008)CrossRefGoogle Scholar
  10. 10.
    Lu, H., Pan, W., Lane, N.D., Choudhury, T., Campbell, A.T.: SoundSense: Scalable Sound Sensing for People-Centric Applications on Mobile Phones. In: Proceedings of the 7th International Conference on Mobile systems, Applications, and Services, pp. 165–178 (2009)Google Scholar
  11. 11.
    Borst, J.P., Taatgen, N.A., Van Rijn, H.: The problem state: A Cognitive Bottleneck in Multitasking. J. Exp. Psychol. Learn. Mem. Cognit. 36(2), 363–382 (2010)CrossRefGoogle Scholar
  12. 12.
    Monk, C.A., Boehm-Davis, D.A., Trafton, J.G.: Recovering from Interruptions: Implications for Driver Distraction Research. Hum. Factors 46, 650–663 (2004)CrossRefGoogle Scholar
  13. 13.
    Iqbal, S.T., Bailey, B.P.: Leveraging Characteristics of Task Structure to Predict Costs of Interruption. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 741–750. ACM, New York (2006)CrossRefGoogle Scholar
  14. 14.
    Tanaka, T., Fujita, K.: Study of User Interruptibility Estimation Based on Focused Application Switching. In: Proceedings of the ACM 2011 Conference on Computer Supported Cooperative Work, pp. 721–724. ACM, New York (2011)CrossRefGoogle Scholar
  15. 15.
    Juang, C.-F., Cheng, C.-N., Tu, C.-C.: Wavelet Energy-Based Support Vector Machine for Noisy Word Boundary Detection with Speech Recognition Application. Expert Syst. Appl. 36(1), 321–332 (2009)CrossRefGoogle Scholar
  16. 16.
    Juang, C.-F., Cheng, C.-N., Che, T.-M.: Speech detection in Noisy Environments by Wavelet Energy-based Recurrent Neural Fuzzy Network. Expert Syst. Appl. 36(1) (2009)Google Scholar
  17. 17.
    Tanaka, T., Fukasawa, S., Takeuchi, K., Nonaka, M., Fujita, K.: Study of Uninterruptibility Estimation Method for Office Worker during PC Work. Inform. Process. Soc. Jpn. 53(1), 126–137 (2012) (in Japanese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Satoshi Hashimoto
    • 1
  • Takahiro Tanaka
    • 1
  • Kazuaki Aoki
    • 1
  • Kinya Fujita
    • 1
  1. 1.Graduate SchoolTokyo University of Agriculture and TechnologyKoganeiJapan

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