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Learning Nouns and Adjectives: A Connectionist Account

Michael Gasser
Computer Science and Linguistics Departments
Lindley Hall 215
Indiana University
Bloomington, IN 47405, USA
gasser@indiana.edu - Linda B. Smith
Psychology Department
Psychology 332
Indiana University
Bloomington, IN 47405, USA
smith4@indiana.edu

Abstract:

Why do children learn nouns such as cup faster than dimensional adjectives such as big? Most explanations of this phenomenon rely on prior knowledge of the noun-adjective distinction or on the logical priority of nouns as the arguments of predicates. In this paper we examine an alternative account, one which relies instead on properties of the semantic categories to be learned and of the word learning task itself. We isolate four such properties: the relative size, the relative compactness, and the degree of overlap of the regions in representational space associated with the categories and the presence or absence of lexical dimensions ( what color?) in the linguistic context of a word. In a set of five experiments, we trained a simple connectionist network to label input objects in particular linguistic contexts. The network learned categories resembling nouns with respect to the four properties faster than it learned categories resembling adjectives.

Young children learn nouns more rapidly and less errorfully than they learn adjectives. The nouns that children so readily learn typically label concrete things such as BLOCK and DOG. The adjectives that young children learn with greater difficulty label the perceptible properties of these same objects, for example, RED and WET. Why are concrete nouns easier for young children to learn than dimensional adjectives?

It is common in the study of cognitive development to explain such differences in learning by positing domain-specific mechanisms dedicated to that learning. Thus one might explain the noun advantage by looking for conceptual structures that specifically constrain or promote the learning of nouns and the lack of such specific structures for adjectives. In this paper, we pursue an alternate idea. We propose that common nouns and dimensional adjectives are initially acquired by the very same processes in the very same way. But, we argue, many mundane factors conspire to make names for common things more easily learned than labels for the properties of those things. We test our account by examining how a general category learning device, a multi-layer feedforward connectionist network, learns concrete nouns and dimensional adjectives.

Next: The Phenomenon

Michael Gasser
Fri Dec 6 13:15:34 EST 1996