Grounding language in perception: A connectionist model of spatial terms and vague quantifiers

This paper presents a new comtectionist model of spatial language based on real psycholinguistic data. It puts together various constraints on object knowledge ("what") and on object localisation ("where") in order to influence the comprehension of a range of linguistic terms, mirroring what participants do in experiments. ne computational model consists of a vision processing module for input scenes, an Elman network module for the representation of object dynamics, and a dual-route network for the production of object names and linguistic prepositions describing the scene. Preliminary simulations on the prediction of spatial term ratings are presented, and extensions of the model to vague quantifiers and other syntactic categories are considered.