creators_name: Martinez, Guillermina creators_name: Cangelosi, Angelo creators_name: Coventry, Kenny type: confposter datestamp: 2002-01-11 lastmod: 2011-03-11 08:54:52 metadata_visibility: show title: A Hybrid Neural Network and Virtual Reality System for Spatial Language Processing ispublished: pub subjects: comp-sci-art-intel subjects: comp-sci-neural-nets subjects: psy-ling full_text_status: public 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 extra-geometrical variables. date: 2001 date_type: published volume: 1 pagerange: 16-21 refereed: TRUE referencetext: [1] Carlson-Radvansky, L.A. & Radvansky, G.A. (1996). The influence of functional relations on spatial term selection. Psychological Science, 7(1), 56-60. [2] Coventry, K.R. (in submission). Spatial prepositions and the instantiation of object knowledge: the case of ‘over’, ‘under’, ‘above’ and ‘below’. [3] Coventry, K.R. (1998). Spatial prepositions, functional relations and lexical specification. In P. Olivier and K. Gapp (Eds.), The Representation and Processing of Spatial Expressions, pp247-262. Lawrence Erlbaum Associates. [5] Coventry. K.R., Carmichael, R. & Garrod, S.C. (1994). Spatial prepositions, functional relations and task requirements. Journal of Semantics, 11, 289-309. [4] Coventry, K.R., Prat-Sala, M. & Richards, L. (2001). The interplay between geometry and function in the comprehension of ‘over’, ‘under’, ‘above’ and ‘below’. Journal of Memory and Language, 44, 376-398. [6] Feldman J., Fanty M. & Goddard N. (1988). Computing with structured neural networks. IEEE Computer, 21, 91-104. [7] Garrod, S.C. & Sanford, A.J. (1989). Discourse models as interfaces between language and the spatial world. Journal of Semantics, 6, 147-160. [8] Harnad S. (1990). The Symbol Grounding Problem. Physica D, 42, 335-346 [9] Harris C. (1990). Connectionism and cognitive linguistics. Connection Science, 2(l), 7-33. [10] Herskovits, A. (1986). Language and spatial cognition. Cambridge University Press. [11] Logan, G.D. & Sadler, D.D. (1996). A computational analysis of the apprehension of spatial relations. In P. Bloom, M. A. Peterson, L. Nadel, & M. Garrett (Eds.), Language and Space, pp 493-529. Cambridge, MA: MIT Press. [12] Regier, T. (1996). The human semantic potential: Spatial language and constrained connectionism. Cambridge, MA: MIT Press. [13] Regier, T. & Carlson, L.A. (in press). Grounding spatial language in perception: An empirical and computational investigation. Journal of Experimental Psychology: General. [14] Talmy, L. (1983). How language structures space. In H. Pick & L. Acredolo (Eds.), Spatial orientation: Theory, research and application (pp. 225-282). New York: Plenum. citation: Martinez, Guillermina and Cangelosi, Angelo and Coventry, Kenny (2001) A Hybrid Neural Network and Virtual Reality System for Spatial Language Processing. [Conference Poster] document_url: http://cogprints.org/2019/3/martinez-ijcnn-cameraready.pdf