Abstract
From at least two months onwards, infants can form perceptual categories. During the first year of life, object knowledge develops from the ability to represent individual object features to representing correlations between attributes and to integrate information from different sources. At the end of the first year, these representations are shaped by labels, opening the way to conceptual knowledge. Here, we review the development of object knowledge and object categorization over the first year of life. We then present an artificial neural network model that models the transition from early perceptual categorization to categories mediated by labels. The model informs a current debate on the role of labels in object categorization by suggesting that although labels do not act as object features they nevertheless affect perceived similarity of perceptually distinct objects sharing the same label. The model presents the first step of an integrated account from early perceptual categorization to language-based concept learning.
Highlights
During their first 2 years of life, infants move from the vast array of seemingly disconnected sensory experiences towards a sophisticated knowledge of objects, people and events, including the ability to group perceptually different objects into common categories, and to understand and produce the names for many of them [1,2]
We aim to present a first step towards an integrated account of semantic development in the form of a computer model that accounts for phenomena in early prelinguistic categorization as well as for the role of word learning on category structures
The extended model had the same architecture as the original one, but in order to model the transition from prelinguistic perceptual categorization to language-mediated categorization we extended the model with task/label units linked to the hidden layer of the cortical memory system
Summary
During their first 2 years of life, infants move from the vast array of seemingly disconnected sensory experiences towards a sophisticated knowledge of objects, people and events, including the ability to group perceptually different objects into common categories, and to understand and produce the names for many of them [1,2]. Two closely related areas of research have addressed infants’ developing knowledge about individual objects, and the ability to form object categories, respectively. Usually concerned with infants and toddlers from 14 months of age, has focused on when and how words are learned, how they are linked to objects, how they are used and extended to novel objects and how knowledge of a label affects children’s inferences about an object’s hidden properties. A second strand, usually focusing on younger infants around 10–12 months of age, addresses the question of how labels affect infants’ categorization of objects that share the same label or that are labelled differently. We aim to present a first step towards an integrated account of semantic development in the form of a computer model that accounts for phenomena in early prelinguistic categorization as well as for the role of word learning on category structures. In the second part of the paper, we present a computational model that has previously been used to account for apparently contradictory results in early object categorization, and we enhance it to account for the transition from prelinguistic to language-mediated object categorization
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