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The efficiency of multimodal interaction for a map-based task

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Published:29 April 2000Publication History

ABSTRACT

This paper compares the efficiency of using a standard direct-manipulation graphical user interface (GUI) with that of using the QuickSet pen/voice multimodal interface for supporting a military task. In this task, a user places military units and control measures (e.g., various types of lines, obstacles, objectives) on a map. Four military personnel designed and entered their own simulation scenarios via both interfaces. Analyses revealed that the multimodal interface led to an average 3.5-fold speed improvement in the average entity creation time, including all error handling. The mean time to repair errors also was 4.3 times faster when interacting multimodally. Finally, all subjects reported a strong preference for multimodal interaction. These results indicate a substantial efficiency advantage for multimodal over GUI-based interaction during map-based tasks.

References

  1. Chapanis, A., Ochsman, R. B., Parrish, R. N., Weeks, G. D., Studies in interactive communication: I. The effects of four communication modes on the behavior of teams during cooperative problem solving. Human Factors, 1972. 14: pp. 487--509.Google ScholarGoogle ScholarCross RefCross Ref
  2. Cohen, P. R., Dalrymple, M., Moran, D. B., Pereira, F., Sullivan, J., Gargan, R., Schlossberg, J., and Tyler, S., Synergistic use of natural language and direct manipulation, in Proc. of the Human-Factors in Computing Systems Con-ference (CHI'89). 1989, ACM Press: New York, pp. 227--234. Google ScholarGoogle Scholar
  3. Cohen, P. R., Johnston, M., McGee, D., Oviatt, S., Clow, J., and Smith, I., The efficiency of multimodal interaction: A case study, in the Proceedings of the 5th International Conference on Spoken Language Processing, Sydney, Australia, 1998, 2: pp. 249--252.Google ScholarGoogle Scholar
  4. Cohen, P. R., Johnston, M., McGee, D., Oviatt, S., Pittman, J., Smith, I., Chen, L., Clow, J., QuickSet: Multimodal interaction for distributed applications, in Proc. of the Fifth ACM International Multmedia Conference, E. Glinert, Editor. 1997, ACM Press: New York. pp. 31--40. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Cohen, P.R., McGee, D., Oviatt, S., Wu, L., Clow, J., King, R., Julier, S., Rosenblum, L., Multimodal Interaction for 2D and 3D Environments. IEEE Computer Graphics and Applications, 1999. 19(4): pp. 10--13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Cohen, P.R. and Oviatt, S.L., The Role of Voice Input for Human-Machine Communication. Proc. of the National Academy of Sciences, 1995. 92: pp. 9921--9927.Google ScholarGoogle ScholarCross RefCross Ref
  7. Courtemanche, A.J., Ceranowicz, A., ModSAF Development Status., in the Proc. of the Fifth Con-ference on Computer Generated Forces and Behavioral Representation, Orlando, 1995, Univ. of Central Florida, pp. 3--13.Google ScholarGoogle Scholar
  8. Johnston, M., Cohen, P. R., McGee, D., Oviatt, S. L., Pittman, J. A., Smith., I. Unification-based multimodal integration., in the Proc. of the 35th Annual Meeting of the Association for Computational Linguistics (ACL) and 8th Conference of the European Chapter of the ACL, 1997, pp. 281--288. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Karat, C., Halverson, C., Horn, D., and Karat, J., Patterns of entry and correction in large vocabulary continuous speech recognition systems, in the Proc. of Human Factors in Com-puting Systems, New York, 1999, ACM Press, pp. 568--575. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Martin, G.L., The utility of speech input in user-computer interfaces. International Journal of Man-machine Studies, 1989. 30(4): pp. 355--375. aR@<11>McGee, D., Cohen, P.R., and Oviatt, S.L., Confirmation in Multimodal Systems, in Proc. of the 17th International Conference on Computational Linguistics (COLING '98) and 36th Annual Meeting of the Association for Computational Linguistics (ACL'98). 1998: Montreal, Canada. pp. 823--829. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Moore, R., Dowding, J., Bratt, H., Gawron, J., Gorfu, Y., Cheyer, A., CommandTalk: A Spoken-Language Interface for Battlefield Simulations, Proc. of the 5th Conference on Applied Natural Language Processing, Association for Computational Linguistics, 1997: Washington, DC. pp. 1--7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Oviatt, S. L., Pen/Voice: Complementary multimodal communication, Proc. of Speech Tech'92, New York, 238--241Google ScholarGoogle Scholar
  13. Oviatt, S.L., Multimodal interactive maps: Designing for human performance. Human Computer Interaction, 1997. 12: pp. 93--129. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Oviatt, S.L., Mutual disambiguation of recognition errors in a multimodal architecture, in the Proc. of the Conference on Human Factors in Computing System, New York, 1999, ACM Press, pp. 576--583. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Oviatt, S.L., Cohen, P. R., 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 gesture applications: State-of-the-art systems and research directions for 2000 and beyond. In submission.Google ScholarGoogle Scholar
  16. Pausch, R. and Leatherby, J. H., A study comparing mouse-only vs. mouse-plusvoice input for a graphical editor, Journal of the American Voice Input/Output Society, 9:2, July, 1991, pp 55--66Google ScholarGoogle Scholar
  17. Rudnicky, A.I., Mode Preference in a simple data-retrieval task, in ARPA Human Language Technology Workshop. March 1993: Princeton, New Jersey. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Suhm, B., Myers, B., and Waibel, A., Model-based and empirical evaluation of multimodal interactive error correction, in the Proc. of the Conf. on Human Factors in Computing Systems, New York, 1999, ACM Press, 584--591. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Shneiderman, B., Natural vs. precise concise languages for human operation of computers: Research issues and experimental approaches. Proceedings of the 18th Annual Meeting of the Association for Computational Linguistics, and Parasession on Topics in Interactive Discourse, Univ. of Pennsylvania, June, 1980, pp. 139--141. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Wickens, C., Sandry, D., and Vidulich, M., Compatibility and resource competition between modalities of input, central processing, and output. Human Factors, 1983. 25(2): pp. 227--248.Google ScholarGoogle ScholarCross RefCross Ref
  21. Wu, L., Oviatt, S., L. and Cohen, P. R., Statistical multimodal integration for intelligent HCI, in Neural Networks for Signal Processing, Y.H. Hu, Larsen, J., Wilson, E., and Douglas, S., Editors. 1999, IEEE Press: New York. pp. 487--496.Google ScholarGoogle Scholar
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    • Published in

      cover image DL Hosted proceedings
      ANLC '00: Proceedings of the sixth conference on Applied natural language processing
      April 2000
      344 pages

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      Association for Computational Linguistics

      United States

      Publication History

      • Published: 29 April 2000

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