Connectionist Modeling of Linguistic Quantifiers

Rajapakse, R.K., Cangelosi, A., Coventry, K.R. ORCID: https://orcid.org/0000-0003-2591-7723, Newstead, S. and Bacon, A. (2005) Connectionist Modeling of Linguistic Quantifiers. In: Artificial Neural Networks: Formal Models and Their Applications. Lecture Notes in Computer Science, 3697 . Springer, Berlin Heidelberg, pp. 679-684. ISBN 978-3540287551

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Abstract

This paper presents a new connectionist model of the grounding of linguistic quantifiers in perception that takes into consideration the contextual factors affecting the use of vague quantifiers. A preliminary validation of the model is presented through the training and testing of the model with experimental data on the rating of quantifiers. The model is able to perform the “psychological” counting of objects (fish) in visual scenes and to select the quantifier that best describes the scene, as in psychological experiments.

Item Type:	Book Section
Faculty \ School:	Faculty of Social Sciences > School of Social Work and Psychology (former - to 2012) Faculty of Social Sciences > School of Psychology
UEA Research Groups:	Faculty of Social Sciences > Research Groups > Cognition, Action and Perception
Depositing User:	Pure Connector
Date Deposited:	17 May 2016 16:01
Last Modified:	24 Sep 2024 07:45
URI:	https://ueaeprints.uea.ac.uk/id/eprint/58820
DOI:	10.1007/11550907_108

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