2024-03-29T15:01:15Z
https://nagoya.repo.nii.ac.jp/oai
oai:nagoya.repo.nii.ac.jp:00007746
2023-01-16T03:53:17Z
320:321:322
Mental Tension Detection in the Speech based on physiological monitoring
Ariga, Michiaki
Yano, Yoshikazu
Doki, Shinji
Okuma, Shigeru
open access
Copyright © 2007 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or 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 must be obtained from the IEEE by writing to pubs-permissions@ieee.org.
The focus of this paper is mental tension detection in speech to assist control the tension in day-to-day business such as conferences and operations in a call center. It is difficult to use classical techniques for mental tension detection in day-to-day business because those techniques require invasion body by electrodes or squirts and tied up by cables. In order to achieve a non-invasive, non-contact and low-restricting method, this proposed technique uses acoustic features in the speech. The technique uses the vocal tract model which represents the shape and the tightness of throat muscle. The Gaussian Mixture Model (GMM) classifies two mental tension states: high-tension and non-tension. The experiment result shows high recognition rate of mental tension detection.
IEEE
2007
eng
journal article
VoR
http://hdl.handle.net/2237/9466
https://nagoya.repo.nii.ac.jp/records/7746
https://doi.org/10.1109/ICSMC.2007.4414150
978-1-4244-0991-4
IEEE International Conference on Systems, Man and Cybernetics
2022
2027
https://nagoya.repo.nii.ac.jp/record/7746/files/doki_1.pdf
application/pdf
190.5 kB
2018-02-19