Natural Language Processing Research

Our research in Natural Language Processing aims at bridging the gap between subsymbolic representations and complex high-level behavior. The models are based on subsymbolic mechanisms but aim at explaining how people learn word meanings, organize their lexicon, understand sentences and stories, and answer questions about them. An important aspect of this research is also understanding linguistic disorders, and most recently, the evolution of language.

This research is supported by NIH under NRSA 1F32DC00459-01 and previously by Texas Higher Education Coordinating Board under grant ARP-003658-444-1995. Most of our projects are described below; for more details and for other projects, see publications in Natural Language Processing.

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