Abstract

Studies of the categorical perception (CP) of sensory continua have a long and rich history in psychophysics. In 1977, Macmillan et al. introduced the use of signal detection theory to CP studies. Anderson et al. simultaneously proposed the first neural model for CP, yet this line of research has been less well explored. In this paper, we assess the ability of neural-network models of CP to predict the psychophysical performance of real observers with speech sounds and artificial/novel stimuli. We show that a variety of neural mechanisms is capable of generating the characteristics of categorical perception. Hence, CP may not be a special mode of perception but an emergent property of any sufficiently powerful general learning system. Neural Models of CP 3 Neural Network Models of Categorical Perception Studies of the categorical perception (CP) of sensory continua have a long and rich history. For a comprehensive review up until a decade ago, see the volume edited by Harnad (1987). ...

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