Fluency: Time for a Paradigm Shift

Pauses in spontaneous speaking constitute a rich source of data for several disciplines. They have been used to enhance automatic segmentation of speech, classification of patients with acquired communication disorders, the design of psycholinguistic models of speaking, and the analysis of psychological disorders. Unfortunately, however, although pause analysis has been with us for more than 40 years, their interpretation has been compromised by several problems [6]. The first problem is that the pause distribution is skewed, making mean duration a poor measure of central tendency. The second problem is that there are at least two components to the pause duration distribution, a problem that has been confounded by the fact that most authors have assumed that short pauses can be ignored. The third problem is that many scholars have used an arbitrary criterion to separate the pause components, thereby adopting statistics that reflect errors of commission or omission. In this paper we review recent work that resolves each of these issues and illustrates the application of the new paradigm to a variety of problems. Our research indicates that, first, there are at least two pause duration distributions, each of which may be sensitive to theoretically interesting variables; second, the distributions are log-normal, thereby opening the way to appropriate measures of central tendency and dispersion, and, third, the distributions can be reliably separated by application of signal detection theory, and the proportion of misclassifications minimised and estimated. This paper reviews recent research using the new approach to pause analysis.