Syntagmatic and paradigmatic states in spoken word recognition

Abstract

The process of spoken word recognition has frequently been characterized as a mapping of information through a multidimensional space, the dimensions of which correspond to time and acoustic-phonetic similarity. Within this framework, the speed and accuracy of spoken word recognition is a direct function of the ease of traversing a path through the space. The traversal of a path may be affected by at least two states of the space at any point in processing: The first, or syntagmatic, state refers to the history and future of the path. The syntagmatic states of a word correspond to its ‘‘probabilistic’’ phonotactics. The second, or paradigmatic, state refers to the degree of activation within the space at any point (or what has previously been referred to as ‘‘neighborhood activation’’). A connectionist instantiation will be presented of this framework that attempts to predict the speed and accuracy of spoken word recognition as function of syntagmatic and paradigmatic states. Also discussed is a number of empirical tests of the model that provide further insights into the roles of phonotactics and neighborhood structure in spoken word recognition. [Work supported by NIH Grant No. DC-00879-01 to the State University of New York at Buffalo.]