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Modelling the transition from perceptual to conceptual organization

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Abstract

We present a neural network model of the transition from early, perceptually-based category formation to conceptual categorization based on the learning of category labels. The model investigates the interactions between category structure and labelling success in terms of category compactness, between-category similarity, frequency of labelling and prelinguistic object knowledge. By providing accounts both of the effect of category structure on word learning and of word learning on category structure the model presents the first step of a unified account of category and word learning.