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Rewiring lexical networks on the fly.
In Eurospeech 91: Proceedings of the 2nd European Conference on Speech Communication and Technology, Vol. 1 (pp. 117-120). Genova, Italy, 24-26 September.
Year of publication:
A back-propagation network with recurrent connections can successfully model many aspects of human spoken word recognition (Norris, 1988, 1990). However, the network is unable to revise its decisions in the light of subsequent context. TRACE (McClelland & Elman, 1986), on the other hand manages to deal appropriately with following context but only by using a highly implausible architecture that fails to account for some important experimental results. A new model is presented which combines the more desirable properties of these two models. In contrast to TRACE the model is entirely bottom-up and can readily perform simulations with vocabularies of tens of thousands of words.