Summary: ToappearinProceedingsofthe12thConferenceonComputationalNaturalLanguageLearning(CoNLL2008),Manchester,UK.
Fast Mapping in Word Learning: What Probabilities Tell Us
Afra Alishahi and Afsaneh Fazly and Suzanne Stevenson
Department of Computer Science
University of Toronto
{afra,afsaneh,suzanne}@cs.toronto.edu
Abstract
Children can determine the meaning of a
new word from hearing it used in a familiar
context--an ability often referred to as fast
mapping. In this paper, we study fast map-
ping in the context of a general probabilistic
model of word learning. We use our model
to simulate fast mapping experiments on chil-
dren, such as referent selection and retention.
The word learning model can perform these
tasks through an inductive interpretation of
the acquired probabilities. Our results suggest
that fast mapping occurs as a natural conse-
quence of learning more words, and provides

Source: Alishahi, Afra - Department of Computational Linguistics and Phonetics, Universität des Saarlandes

Collections: Computer Technologies and Information Sciences