Abstract
Linguistic and philosophical theories of semantics have usually ignored the problem of explaining how the meanings of predicates are initially acquired. In this paper we propose that connectionist models may give a computational account of this process via extracting regularities from perceptual inputs and associating them with one another. We present results from two simple preliminary experiments, one in which a connectionist network associates labels with visual images with no external teacher, and a second in which a network associates simple sentences with with simple sequences of visual images, or “movies“. While these simulations are simply suggestive, they point the way to a more complete model.
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Cottrell, G.W., Bartell, B., Haupt, C. (1990). Grounding Meaning in Perception. In: Marburger, H. (eds) GWAI-90 14th German Workshop on Artificial Intelligence. Informatik-Fachberichte, vol 251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76071-6_35
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DOI: https://doi.org/10.1007/978-3-642-76071-6_35
Publisher Name: Springer, Berlin, Heidelberg
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