Article

Cognitive Computation

, Volume 2, Issue 4, pp 280-284

First online:

A Connectionist Study on the Interplay of Nouns and Pronouns in Personal Pronoun Acquisition

  • Artem KaznatcheevAffiliated withDepartment of Physics and School of Computer Science, McGill University Email author 

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access

Abstract

Cascade-correlation learning is used to model pronoun acquisition in children. The cascade-correlation algorithm is a feed-forward neural network that builds its own topology from input and output units. Personal pronoun acquisition is an interesting non-linear problem in psychology. A mother will refer to her son as you and herself as me, but the son must infer for himself that when he speaks to his mother, she becomes you and he becomes me. Learning the shifting reference of these pronouns is a difficult task that most children master. We show that learning of two different noun-and-pronoun addressee patterns is consistent with naturalistic studies. We observe a surprising factor in pronoun reversal: increasing the amount of exposure to noun patterns can decrease or eliminate reversal errors in children.

Keywords

Computational linguistics Cascade-correlation neural networks Personal pronoun acquisition Computational model