Toward a psycholinguistically-motivated model of language processing

Abstract

Psycholinguistic studies suggest a model of human language processing that 1) performs incremental interpretation of spoken utterances or written text, 2) preserves ambiguity by maintaining competing analyses in parallel, and 3) operates within a severely constrained short-term memory store - possibly constrained to as few as four distinct elements. This paper describes a relatively simple model of language as a factored statistical time-series process that meets all three of the above desiderata; and presents corpus evidence that this model is sufficient to parse naturally occurring sentences using human-like bounds on memory. © 2008. Licensed under the Creative Commons.