A history-taking system that uses continuous speech recognition
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abstract: Q-MED is an automated history-taking system that uses speaker independent continuous speech as its main interface modality. Q-MED is designed to allow a patient to enter her basic symptoms by engaging in a dialog with the program. Error-recovery mechanisms help to eliminate findings resulting from misrecognitions or incorrect parses. An evaluation of the natural language parser that Q-MED uses to map user utterances to findings showed an overall semantic accuracy of 87 percent; Q-MED asks more specific questions to capture findings that were not volunteered, or that were unable to be parsed in their initial, open-ended form.
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| Abstract | Q-MED is an automated history-taking syste … Q-MED is an automated history-taking system that uses speaker independent continuous speech as its main interface modality. Q-MED is designed to allow a patient to enter her basic symptoms by engaging in a dialog with the program. Error-recovery mechanisms help to eliminate findings resulting from misrecognitions or incorrect parses. An evaluation of the natural language parser that Q-MED uses to map user utterances to findings showed an overall semantic accuracy of 87 percent; Q-MED asks more specific questions to capture findings that were not volunteered, or that were unable to be parsed in their initial, open-ended form. parsed in their initial, open-ended form. |
| Address | Washington D.C. + |
| Author | Kevin Johnson +, Alex Poon +, Smadar Shiffman +, Richard Lin +, and Lawrence M. Fagan + |
| Bibtype | techreport + |
| Institution | Knowledge Systems, AI Laboratory + |
| Key | KSL-92-23 + |
| Number | KSL-92-23 + |
| Tag | Computer science + |
| Title | A History-Taking System that Uses Continuous Speech Recognition + |
| Tr id | KSL-92-23 + |
| Year | 1992 + |
