A hybrid neural network and virtual relality system for spatial language processing

G.C. Martinez, A Cangelosi, K.R. Coventry

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper describes a neural network model for the study of spatial language. It deals with both geometric and functional variables, which have been shown to play an important role in the comprehension of spatial prepositions. The network is integrated with a virtual reality interface for the direct manipulation of geometric and functional factors. The training uses experimental stimuli and data. Results
show that the networks reach low training and generalization errors. Cluster analyses of hidden activation show that stimuli primarily group according to extrageometrical variables.
Original languageEnglish
Title of host publicationProceedings of the 2001 International Joint Conference on Neural Networks, Washington DC
PublisherIEEE Press
Pages16-21
Number of pages6
Volume1
Publication statusPublished - 2001

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