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A continuous-speech interface to a decision support system: II. An evaluation using a Wizard-of-Oz experimental

W M Detmer1, S Shiffman, J C Wyatt

  • 1Section on Medical Informatics, Stanford University School of Medicine, CA 94305-5479.

Journal of the American Medical Informatics Association : JAMIA
|January 1, 1995
PubMed
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A continuous-speech interface for decision support systems achieved 81% semantic accuracy, even with speech recognition errors below 50%. Language processing techniques improved performance, demonstrating the utility of the Wizard-of-Oz design for evaluating speech input systems.

Area of Science:

  • Medical Informatics
  • Human-Computer Interaction
  • Speech Recognition Technology

Background:

  • Continuous-speech interfaces offer potential for efficient interaction with medical decision support systems.
  • Evaluating the accuracy of these interfaces is crucial for their clinical adoption.
  • Previous methods may not fully capture real-world performance nuances.

Purpose of the Study:

  • To evaluate the performance of a continuous-speech interface linked to a medical decision support system.
  • To assess both speech recognition accuracy and the semantic accuracy of term matching.
  • To explore the effectiveness of a Wizard-of-Oz experimental design in this evaluation.

Main Methods:

  • A prospective evaluation using a Wizard-of-Oz experimental design.

Related Experiment Videos

  • Physicians spoke utterances describing clinical findings into a speech interface.
  • Utterances were matched against controlled-vocabulary terms from Quick Medical Reference (QMR).

    • Main Results:

    • Overall speech recognition accuracy was below 50%.
    • Semantic accuracy, using keyword matching language-processing techniques, reached 81%.
    • The Wizard-of-Oz design facilitated a robust evaluation.

    Conclusions:

    • Language processing techniques can significantly improve semantic accuracy despite speech misrecognition.
    • The Wizard-of-Oz experimental design is a valuable method for evaluating speech-input systems.
    • This approach holds promise for future development and assessment of voice-enabled medical technologies.