Conference: Perceptrons and Syntactic Structures at 60: Computational Modeling of Language

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

This workshop will bring together leading researchers in cognitive science and artificial intelligence who specialize in the integration of linguistic theory with statistical approaches, especially neural networks. Neural networks have been important in many of the recent advances in language technologies (in what's called "deep learning"), and the greater integration of linguistic structure into these models promises to lead to further breakthroughs. The main focus of this meeting will be on how integration of models of linguistic structure with probabilistic learning theories may lead to a deeper understanding of the way that humans process and represent language. This sort of integration has been difficult to achieve in the past in part because of the separation of researchers in each tradition into different disciplines interacting in different conferences. In-depth analysis of the structure of human languages is conducted in mostly in Linguistics, while neural network modeling and other statistical learning research is conducted mostly in Psychology and Computer Science. The workshop will be held as part of the inaugural meeting of the Society for Computation in Linguistics, taking place concurrently with the meeting of the Linguistic Society of America. It will thus bring researchers from other disciplines into contact with linguists, and will stimulate productive intellectual exchange.