Prediction, explanation, and the role of generative models in language processing.Thomas A. Farmer,Meredith Brown &Michael K. Tanenhaus -2013 -Behavioral and Brain Sciences 36 (3):211-212.detailsWe propose, following Clark, that generative models also play a central role in the perception and interpretation of linguistic signals. The data explanation approach provides a rationale for the role of prediction in language processing and unifies a number of phenomena, including multiple-cue integration, adaptation effects, and cortical responses to violations of linguistic expectations.
Syllable Inference as a Mechanism for Spoken Language Understanding.Meredith Brown,Michael K. Tanenhaus &Laura Dilley -2021 -Topics in Cognitive Science 13 (2):351-398.detailsA classic problem in cognitive science concerns how listeners perceive and understand speech as comprised of discrete words. We propose a Syllable Inference account of spoken word recognition and segmentation, under which alternative hierarchical models of syllables, words, and phonemes are dynamically posited from cues that include current and past speech rate, with a goal of maximal prediction of sensory input. Three experiments using the Visual World eye‐tracking paradigm provide evidence supporting our proposal.