Please use this identifier to cite or link to this item: doi:10.22028/D291-30849
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Title: Counting ‘uhm’s: How tracking the distribution of native and non-native disfluencies influences online language comprehension
Author(s): Bosker, Hans Rutger
van Os, Marjolein
Does, Rik
van Bergen, Geertje
Language: English
Title: Journal of memory and language : JML
Volume: 106
Startpage: 189
Endpage: 202
Publisher/Platform: Elsevier
Year of Publication: 2019
Publikation type: Journal Article
Abstract: Disfluencies, like uh, have been shown to help listeners anticipate reference to low-frequency words. The associative account of this ‘disfluency bias’ proposes that listeners learn to associate disfluency with low-frequency referents based on prior exposure to non-arbitrary disfluency distributions (i.e., greater probability of low-frequency words after disfluencies). However, there is limited evidence for listeners actually tracking disfluency distributions online. The present experiments are the first to show that adult listeners, exposed to a typical or more atypical disfluency distribution (i.e., hearing a talker unexpectedly say uh before high-frequency words), flexibly adjust their predictive strategies to the disfluency distribution at hand (e.g., learn to predict high-frequency referents after disfluency). However, when listeners were presented with the same atypical disfluency distribution but produced by a non-native speaker, no adjustment was observed. This suggests pragmatic inferences can modulate distributional learning, revealing the flexibility of, and constraints on, distributional learning in incremental language comprehension.
DOI of the first publication: 10.1016/j.jml.2019.02.006
URL of the first publication:
Link to this record: hdl:20.500.11880/29173
ISSN: 1096-0821
Date of registration: 20-May-2020
Faculty: P - Philosophische Fakultät
Department: P - Sprachwissenschaft und Sprachtechnologie
Professorship: P - Keiner Professur zugeordnet
Collections:UniBib – Die Universitätsbibliographie

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