The processing of pseudoword form and meaning in production and comprehension: A computational modeling approach using linear discriminative learning.

ABSTRACT: Pseudowords have long served as key tools in psycholinguistic investigations of the lexicon. A common assumption underlying the use of pseudowords is that they are devoid of meaning: Comparing words and pseudowords may then shed light on how meaningful linguistic elements are processed differently from meaningless sound strings. However, pseudowords may in fact carry meaning. On the basis of a computational model of lexical processing, linear discriminative learning (LDL Baayen et al., Complexity, 2019, 1-39, 2019), we compute numeric vectors representing the semantics of pseudowords. We demonstrate that quantitative measures gauging the semantic neighborhoods of pseudowords predict reaction times in the Massive Auditory Lexical Decision (MALD) database (Tucker et al., 2018). We also show

SUBMITTER: Chuang YY 

PROVIDER: S-EPMC8219637 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature