Automatic stress detection in emergency (telephone) calls
by Iulia Lefter, Leon J.M. Rothkrantz, David A. Van Leeuwen, Pascal Wiggers
International Journal of Intelligent Defence Support Systems (IJIDSS), Vol. 4, No. 2, 2011

Abstract: The abundance of calls to emergency lines during crises is difficult to handle by the limited number of operators. Detecting if the caller is experiencing some extreme emotions can be a solution for distinguishing the more urgent calls. Apart from these, there are several other applications that can benefit from awareness of the emotional state of the speaker. This paper describes the design of a system for selecting the calls that appear to be urgent, based on emotion detection. The system is trained using a database of spontaneous emotional speech from a call-centre. Four machine learning techniques are applied, based on either prosodic or spectral features, resulting in individual detectors. As a last stage, we investigate the effect of fusing these detectors into a single detection system. We observe an improvement in the equal error rate (EER) from 19.0% on average for four individual detectors to 4.2% when fused using linear logistic regression. All experiments are performed in a speaker independent cross-validation framework.

Online publication date: Sat, 28-Feb-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Defence Support Systems (IJIDSS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com