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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 gen-erating
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.
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given: R.I.
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- family: Harnad
given: S.R.
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date: 2000
date_type: published
datestamp: 2001-06-19
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keywords: 'categorical perception, neural networks'
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referencetext: |-
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title: Neural Network Models of Categorical Perception
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