Cart (Loading....) | Create Account
Close category search window

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Kurisu, M. ; Grad. Sch. of Inf. Sci., Hiroshima City Univ., Hiroshima, Japan ; Mera, K. ; Wada, R. ; Kurosawa, Y.
more authors

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

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.