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Multimodal encoding of motion events in speech, gesture and cognition

Published online by Cambridge University Press:  15 December 2023

Ercenur Ünal*
Affiliation:
Department of Psychology, Ozyegin University, Istanbul, Türkiye
Ezgi Mamus
Affiliation:
Multimodal Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands Centre for Language Studies, Radboud University, Nijmegen, The Netherlands
Aslı Özyürek
Affiliation:
Multimodal Language Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands Centre for Language Studies, Radboud University, Nijmegen, The Netherlands Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
*
Corresponding author: Ercenur Ünal; Email: ercenur.unal@ozyegin edu.tr
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Abstract

How people communicate about motion events and how this is shaped by language typology are mostly studied with a focus on linguistic encoding in speech. Yet, human communication typically involves an interactional exchange of multimodal signals, such as hand gestures that have different affordances for representing event components. Here, we review recent empirical evidence on multimodal encoding of motion in speech and gesture to gain a deeper understanding of whether and how language typology shapes linguistic expressions in different modalities, and how this changes across different sensory modalities of input and interacts with other aspects of cognition. Empirical evidence strongly suggests that Talmy’s typology of event integration predicts multimodal event descriptions in speech and gesture and visual attention to event components prior to producing these descriptions. Furthermore, variability within the event itself, such as type and modality of stimuli, may override the influence of language typology, especially for expression of manner.

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Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press