A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment

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KSL-94-38 +  redirect page

A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment +  Has identifier

A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment +  Ksl tr id

A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment +  Number

A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment

Bibtype  techreport

Has publishing details  1994

Has title  A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment

Has year  1994

Title  A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment

Year  1994

Abstract  Objective: Evaluate the performance of a Objective: Evaluate the performance of a continuous-speech interface to a decision-support system.Design: We performed a prospective evaluation of a speech interface that matches unconstrained utterances of physicians with controlled-vocabulary terms from Quick Medical Reference (QMR). We assessed the performance of the speech interface in two stages: in the real-time experiment, physician-subjects viewed audio-visual stimuli intended to evoke clinical findings, spoke a description of each finding into the speech interface, and then chose from a list generated by the interface the QMR term that most closely matched the finding. Subjects believed that the speech recognizer decoded their utterances; in reality, a hidden experimenter typed utterances into the interface (Wizard-of-Oz experimental design). Later, we replayed the same utterances through the speech recognizer and measured how accurately utterances matched with appropriate QMR terms using the results of the real-time experiment as the gold standard.Measurements: We measured how accurately the speech-recognition system converted input utterances to text strings (recognition accuracy) and how accurately the speech interface matched input utterances to appropriate QMR terms (semantic accuracy). Results: Overall recognition accuracy was less than 50%. However, using language-processing techniques that match keywords in recognized utterances to keywords in QMR terms, the semantic accuracy of the system was 81%. Conclusions: We found that reasonable semantic accuracy can be attained when language-processing techniques are used to accommodate for speech misrecognition. We also found that the Wizard-of-Oz experimental design offered many advantages for this evaluation and believe that this technique may be useful to future evaluators of speech-input systems. future evaluators of speech-input systems.

Author  William M. Detmer and Smadar Shiffman and Jeremy C. Wyatt and Charles P. Friedman and Christopher D. Lane and Lawrence M. Fagan +

Has author  William M. Detmer and Smadar Shiffman and Jeremy C. Wyatt and Charles P. Friedman and Christopher D. Lane and Lawrence M. Fagan +

Has identifier  A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment +

Institution  Knowledge Systems, AI Laboratory +

Ksl tr id  A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment +

Note  Updated February 1995. +

Number  A Continuous-Speech Interface to a Decision-Support System: II. An Evaluation Using a Wizard-of-Oz Experiment +

Process note  YES +

Categories  KSL Technical Report +, Publication +, Technical Report +

 

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