Recognition of Psychologically Relevant Aspects of Context on the Basis of Features of Speech

Abstract

Abstract. Especially with mobile systems, one important part of the context of use involves psychological variables like cognitive load and time pressure. This abstract looks at one possible way of capturing such aspects of context: the analysis of features of the users ’ speech. In a replication and extension of an earlier study of our group, we created four experimental conditions that varied in terms of whether the user was (a) navigating within a simulated airport terminal or standing still; and (b) subject to time pressure or not. The speech produced by these subjects was coded in terms of 7 variables. We trained dynamic Bayesian networks on the resulting data in order to see how well the information in the users ’ speech could serve as evidence as to which condition the user had been in. The results give information about the accuracy that can be attained in this way, the methods that can be used to implement the classifiers, and the diagnostic value of some specific features of speech. 1