Title :
Mental tension detection in the speech based on physiological monitoring
Author :
Ariga, Michiaki ; Yano, Yoshikazu ; Doki, Shinji ; Okuma, Shigeru
Author_Institution :
Nagoya Univ., Nagoya
Abstract :
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.
Keywords :
Gaussian processes; physiology; speech processing; Gaussian mixture model; acoustic feature; high-tension speech; mental tension detection; physiological monitoring; vocal tract model; Acoustic signal detection; Autonomic nervous system; Biomedical monitoring; Cables; Control systems; Electrodes; Heart rate; Muscles; Shape; Speech;
Conference_Titel :
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-0990-7
Electronic_ISBN :
978-1-4244-0991-4
DOI :
10.1109/ICSMC.2007.4414150