A Method Using Acoustic Features to Detect Inadequate Utterances in Medical Communication
URI | http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/12034 | ||||||||||||||||||||||||||||||
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File |
IEEESMC2012-final-116.pdf
( 101.0 KB )
Open Date
:2013-05-27
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Title |
A Method Using Acoustic Features to Detect Inadequate Utterances in Medical Communication
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Author |
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Subject |
Mental State
Acoustic Features
Support Vector Machine
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Abstract |
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. |
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Journal Title |
2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC2012)
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Spage |
116
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Epage |
119
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Published Date |
2012
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Language |
eng
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NIIType |
Conference Paper
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Text Version |
著者版
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Rights |
©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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hiroshima-cu
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