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A method using acoustic features to detect inadequate utterances in medical communication

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5 Author(s)
Kurisu, M. ; Grad. Sch. of Inf. Sci., Hiroshima City Univ., Hiroshima, Japan ; Mera, K. ; Wada, R. ; Kurosawa, Y.
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We previously proposed a method that uses grammatical features to detect inadequate utterances of doctors. However, nonverbal information such as that conveyed by gestures, facial expression, and tone of voice are also important. In this paper, we propose a method that uses eight acoustic features to detect three types of mental states (sincerity, confidence, and doubtfulness/acceptance). A Support Vector Machine (SVM) is used to learn these features. Experiments showed that the system's accuracy and recall rates respectively ranged from 0.79-0.91 and 0.80-0.94.

Published in:

Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on

Date of Conference:

14-17 Oct. 2012

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