A back-propagation network with recurrent connections can successfully model many aspects of human spoken word recognition  . However, the network is unable to revise its decisions in the light of subsequent context. TRACE  , 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.
Bibliographic reference. Norris, Dennis (1991): "Rewiring lexical networks on the fly", In EUROSPEECH-1991, 117-120.