Encoding and Verification Effects of Generalized Quantifiers on Working Memory
Aniello De Santo, John Drury
November 2019

A large amount of literature has shown that the type of quantifier used in a sentence significantly affects the verification procedure and the cognitive resources employed to arrive at a truth-judgment. Interestingly, few studies have explored effects of quantifier type on cognitive load during comprehension alone, in order to distinguish between quantifier characterization and verification procedures. In this study, we address this distinction by examining the processing of quantified sentences in an auditory/visual verification task. We show quantifier-type influences on working memory usage as measured by variations in pupil size during encoding and verification, and we relate these results to theories of quantifier meaning grounded in the approximate number system, and to previous results on quantifier complexity based on precise counting strategies. *Comments are more than welcome and can be emailed to the first author*
Format: [ pdf ]
Reference: lingbuzz/004866
(please use that when you cite this article)
Published in: To appear in the Proceedings of CLS 55
keywords: generalized quantifiers, ans, semantic automata, pupillometry, verification, encoding, semantics
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