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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Title
A Method Using Acoustic Features to Detect Inadequate Utterances in Medical Communication
Author
氏名 KURISU Michihisa
ヨミ
別名
氏名 MERA Kazuya
ヨミ
別名
氏名 WADA Ryunosuke
ヨミ
別名
氏名 KUROSAWA Yoshiaki
ヨミ
別名
氏名 TAKEZAWA Toshiyuki
ヨミ
別名
Subject
Mental State
Acoustic Features
Support Vector Machine
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.

Journal Title
2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC2012)
Spage
116
Epage
119
Published Date
2012
Language
eng
NIIType
Conference Paper
Text Version
著者版
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