Connectionist models of language comprehension

Connectionist Models of Language Processing

Traditional approaches to language processing have been based on explicit, discrete representations which are difficult to learn from a reasonable linguistic environment—hence, it has come to be accepted that much of our linguistic representations and knowledge is innate. With its focus on learning based upon graded, malleable, distributed representations, connectionist modeling has reopened th...

Learning to Attend: A Connectionist Model of Situated Language Comprehension

Evidence from numerous studies using the visual world paradigm has revealed both that spoken language can rapidly guide attention in a related visual scene and that scene information can immediately influence comprehension processes. These findings motivated the coordinated interplay account (Knoeferle & Crocker, 2006) of situated comprehension, which claims that utterance-mediated attention cr...

Questions about Connectionist Models of Natural Language

My role as interlocutor for this ACL Forum on Connectionism is to promote discussion by asking questions and making provocative comments. I will begin by asking some questions that I will attempt to answer myself, in order to define some terms. I will then pose some questions for the panel and the audience to discuss, if they are interested, and I will make a few critical comments on the abstra...

Language acquisition also needs non-connectionist models.

Connectionist Models for Natural Language Processing Program

The scientific adequacy of models based on a small number of coarse-grained primitives (e.g. conceptual dependency), popular in AI during the 70's, has been called into question and substantially replaced by a current emphasis in much of computational linguistics on lexicalist models (i.e., ones which use words for representing concepts or meanings). However, few people can doubt that words are...