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Woman or tennis player? Visual typicality and lexical frequency affect variation in object naming

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dc.contributor.author Gualdoni, Eleonora
dc.contributor.author Brochhagen, Thomas
dc.contributor.author Mädebach, Andreas
dc.contributor.author Boleda, Gemma
dc.date.accessioned 2023-03-14T07:16:46Z
dc.date.available 2023-03-14T07:16:46Z
dc.date.issued 2022
dc.identifier.citation Gualdoni E, Brochhagen T, Mädebach A, Boleda G. Woman or tennis player? Visual typicality and lexical frequency affect variation in object naming. Proc Annu Conf Cogn Sci Soc. 2022;44:990-6.
dc.identifier.issn 1069-7977
dc.identifier.uri http://hdl.handle.net/10230/56221
dc.description.abstract Speakers often use different names to refer to the same entity (e.g., “woman” vs. “tennis player”). We here explore factors that affect naming variation for visually presented objects. We analyze a large dataset of object names with realistic images and focus on two factors: visual typicality (of both objects and the contexts they appear in) and name frequency. We develop a novel computational approach to estimate visual typicality, using image representations from Computer Vision models. Specifically, we compute visual typicality as similarity between the representation of an object/context to the average representation of other objects/contexts of its nominal class. In contrast to previous studies, we not only study the name used by most annotators for a given object (top name), but also the second most frequently used (alternative name). Our results show that the top name and the alternative name pull in opposite directions. People’s naming choices are more varied for objects that are less typical for their top name, or more typical for their alternative name. They are also more varied when the top name has relatively low frequency (for alternative names, the opposite effect may be present but the data are not conclusive). Context typicality instead does not show a general effect in our analysis. Overall, our results show that visual and lexical characteristics relating to name candidates beyond the top name are informative for predicting variability in object naming. On a methodological level, we demonstrate the potential of using large scale datasets with realistic images in conjunction with computational methods to inform models of human object naming.
dc.description.sponsorship This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 715154) and the Spanish Research Agency (ref. PID2020-112602GB-I00).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Cognitive Science Society
dc.relation.ispartof Proceedings of the Annual Meeting of the Cognitive Science Society
dc.rights ©2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY).
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.title Woman or tennis player? Visual typicality and lexical frequency affect variation in object naming
dc.type info:eu-repo/semantics/article
dc.subject.keyword object naming
dc.subject.keyword naming variation
dc.subject.keyword visual typicality
dc.subject.keyword object typicality
dc.subject.keyword context typicality
dc.subject.keyword lexical frequency
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/715154
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2020-112602GB-I00
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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