TR#513: Analysis and Classification of Stress Categories from Drivers' Speech

Raul Fernandez and Rosalind W. Picard

In this paper we explore the use of features derived from multiresolution analysis of speech and the Teager Energy Operator for classification of drivers' speech under stressed conditions. The potential stress categories are determined by driving speed and the frequency with which the driver has to solve a mental task while driving. We first use an unsupervised approach to gain some understanding as to whether the discrete stress categories form meaningful clusters in feature space, and use the clustering results to build a user-dependent recognition system which combines local discriminants of 4 discreet stress categories. Recognition results are reported for 4 subjects. Compressed Postscript . PDF . Full list of tech reports