Integrating Form and Meaning: A Distributed Model of Speech Perception

TLDR

The model’s relation to other spoken‑word recognition models is discussed. The study introduces a new distributed connectionist model for spoken‑word perception. The model represents speech by integrating lexical and abstract phonological information, mapping lexical access directly onto this single distributed representation. The model accurately simulates phonetic and lexical decision data from Marslen‑Wilson and Warren (1994) and shows that lexical‑access competition can be interpreted as interference among distributed lexical representations.

Abstract

Abstract We present a new distributed connectionist model of the perception of spoken words. The model employs a representation of speech that combines lexical information with abstract phonological information, with lexical access modelled as a direct mapping onto this single distributed representation. We first examine the integration of partial cues to phonological identity, showing that the model provides a sound basis for simulating phonetic and lexical decision data from Marslen-Wilson and Warren (1994). We then investigate the time course of lexical access, and argue that the process of competition between word candidates during lexical access can be interpreted in terms of interference between distributed lexical representations. The relation between our model and other models of spoken word recognition is discussed.