Advertisement

Long Text Reading in a Car

  • Ladislav Kunc
  • Martin Labsky
  • Tomas Macek
  • Jan Vystrcil
  • Jan Kleindienst
  • Tereza Kasparova
  • David Luksch
  • Zeljko Medenica
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8511)

Abstract

We present here the results of a study focused on text reading in a car. The purpose of this work is to explore how machine synthesized reading is perceived by users. Are the users willing to tolerate deficiencies of machine synthesized speech and trade it off for more current content? What is the impact of listening to it on driver’s distraction? How do the answers to the questions above differ for various types of text content? Those are the questions we try to answer in the presented study. We conducted the study with 12 participants, each facing three types of tasks. The tasks differed in the length and structure of the presented text. Reading out a fable represented an unstructured pleasure reading text. The news represented more structured short texts. Browsing a car manual was an example of working with structured text where the user looks for particular information without much focusing on surrounding content. The results indicate relatively good user acceptance for the presented tasks. Distraction of the driver was related to the amount of interaction with the system. Users opted for controlling the system by buttons on the steering wheel and made little use of the system’s display.

Keywords

Architectures for interaction CUI SUI ad GUI HCI methods and theories Interaction design Speech and natural language interfaces Long text reading car UI LCT 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Brostrom, R., Bengtsson, P., Axelsson, J.: Correlation between safety assessments in the driver-car interaction design process. Applied Ergonomics 42(4), 575–582 (2011)CrossRefGoogle Scholar
  2. 2.
    Cuřín, J., Labský, M., Macek, T., Kleindienst, J., Young, H., Thyme-Gobbel, A., Quast, H., Koenig, L.: Dictating and editing short texts while driving: Distraction and task completion. In: Proceedings of the AutomotiveUI Conference. ACM, New York (2011)Google Scholar
  3. 3.
    Karat, J., Horn, H., Karat, C.: Overcoming unusability: Developing efficient strategies in speech recognition systems. In: Proceedings of CHI 2000 Conference, pp. 141–142. ACM, New York (2000)Google Scholar
  4. 4.
    Kun, A.L., Schmidt, A., Dey, A., Boll, S.: Automotive user interfaces and interactive applications in the car. In: Personal and Ubiquitous Computing, pp. 1–2 (2012)Google Scholar
  5. 5.
    Hart, S.G., Stayeland, L.E.: Development of NASA-TLX (task load index): Results of empirical and theoretical research. In: Hancock, P.A., Meshkati, N. (eds.) Human Mental Workload. North Holland Press, Amsterdam (1988)Google Scholar
  6. 6.
    Pauzié, A.: A method to assess the driver mental workload: The driving activity load index (DALI). IET Intelligent Transport Systems 2(4), 315–322 (2008)CrossRefGoogle Scholar
  7. 7.
    Pauzie, A.: Evaluation of Driver Mental Workload Facing New In-vehicle Information and Communication technology. IET Intelligent Transport Systems, Special Issue – selected papers from HCD (2008)Google Scholar
  8. 8.
    Yun-Cheng, J., Paek, T.: A Voice Search Approach to Replying to SMS Messages. In: Proc: INTERSPEECH 2009, 10th Annual Conference of the Intl. Speech Communication Association, Brighton, United Kingdom (2009)Google Scholar
  9. 9.
    Stefan, M.: The lane-change-task as a tool for driver distraction evaluation. In: Proceedings of the Annual Spring Conference of the GFA/ISOES, vol. 2003 (2003)Google Scholar
  10. 10.
    Labsky, M., Kunc, L., Macek, T., Kleindienst, J., Vystrcil, J.: Recipes for building voice search UIs for automotive. Submitted to EACL 2014 - Dialogue in Motion Workshop, Sweden (2014)Google Scholar
  11. 11.
    Vystrcil, J., Macek, T., Luksch, D., Labsky, M., Kunc, L., Kleindienst, J., Kasparova, T.: Mostly Passive Information Delivery - A Prototype. Submitted to EACL 2014 - Dialogue in Motion Workshop, Sweden (2014)Google Scholar
  12. 12.
    Road vehicles-Ergonomic aspects of transport information and control systems-Simulated lane change test to assess invehicle secondary task demand, International Standard ISO/DIS 26022:2010Google Scholar
  13. 13.
    Brooke, J.: SUS-A quick and dirty usability scale. In: Jordan, P.W., Thomas, B., Weerdmeester, B.A., McClelland, A.L. (eds.) Usability Evaluation in Industry, pp. 189–194. Taylor and Francis, London (1996)Google Scholar
  14. 14.
    Hone, K.S., Graham, R.: Towards a tool for the Subjective Assessment of Speech System Interfaces (SASSI). Natural Language Engineering 6(3-4), 287–303 (2000)CrossRefGoogle Scholar
  15. 15.
    Kubose, T.T., Bock, K., Dell, G.S., Garney, S.M., Kramer, A.F., Mayhugh, J.: The effects of speech production and speech comprehension on simulated driving performance. Applied Cognitive Psychology 20(1), 43–63 (2006)CrossRefGoogle Scholar
  16. 16.
    Drews, F.A., Pasupathi, M., Strayer, D.L.: Passenger and cell phone conversations in simulated driving. Journal of Experimental Psychology: Applied 14(4), 392 (2008)Google Scholar
  17. 17.
    Handley, Z.: Is text-to-speech synthesis ready for use in computer-assisted language learning? Speech Communication 51(10), 906–919 (2009)Google Scholar
  18. 18.
    Viswanathan, M., Viswanathan, M.: Measuring speech quality for text-to-speech systems: Development and assessment of a modified mean opinion score (MOS) scale. Computer Speech & Language Iss. 19(1), 55–83 (2005)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ladislav Kunc
    • 1
  • Martin Labsky
    • 1
  • Tomas Macek
    • 1
  • Jan Vystrcil
    • 1
  • Jan Kleindienst
    • 1
  • Tereza Kasparova
    • 1
  • David Luksch
    • 1
  • Zeljko Medenica
    • 2
  1. 1.IBM Prague Research and Development LabPragueCzech Republic
  2. 2.Nuance Communications, Inc.BurlingtonUSA

Personalised recommendations