Connectionist models of human language processing
Luca Onnis, Morten Christiansen, & Nick Chater
Abstract
Connectionist psycholinguistics is an emerging approach to modeling empirical data on human language processing
using connectionist computational architectures. We review progress made in the area of connectionist
syntactic processing. Constituency, structure dependency, and recursion are notions central to traditional
generative theories of language and are seen as the hallmark of symbolic processing.
Because connectionist models are subsymbolic and their knowledge emerges from large distributed activation
of neuron-like units, their ability to learn and process aspects of syntax represents an important alternative
paradigm in cognitive science. They also invite to rethink traditional notions like the competence/performance
distinction and boundless recursion.
Please email suggestions/errors to lo35@cornell.edu |