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Object naming in language and vision: a survey and a new dataset

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dc.contributor.author Silberer, Carina
dc.contributor.author Zarrieß, Sina
dc.contributor.author Boleda, Gemma
dc.date.accessioned 2021-02-03T11:02:52Z
dc.date.available 2021-02-03T11:02:52Z
dc.date.issued 2020
dc.identifier.citation Silberer C, Zarrieß S, Boleda G. Object naming in language and vision: a survey and a new dataset. In: Calzolari N, Béchet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors. Proceedings of the 12th Language Resources and Evaluation Conference; 2020 May 13-15; Marseilles, France. Stroudsburg (PA): ACL; 2020. p. 5792-801.
dc.identifier.uri http://hdl.handle.net/10230/46318
dc.description Comunicació presentada al 12th Language Resources and Evaluation Conference celebrat del 13 al 15 de maig de 2020 de manera virtual.
dc.description.abstract People choose particular names for objects, such as dog or puppy for a given dog. Object naming has been studied in Psycholinguistics, but has received relatively little attention in Computational Linguistics. We review resources from Language and Vision that could be used to study object naming on a large scale, discuss their shortcomings, and create a new dataset that affords more opportunities for analysis and modeling. Our dataset, ManyNames, provides 36 name annotations for each of 25K objects in images selected from VisualGenome. We highlight the challenges involved and provide a preliminary analysis of the ManyNames data, showing that there is a high level of agreement in naming, on average. At the same time, the average number of name types associated with an object is much higher in our dataset than in existing corpora for Language and Vision, such that ManyNames provides a rich resource for studying phenomena like hierarchical variation (chihuahua vs. dog), which has been discussed at length in the theoretical literature, and other less well studied phenomena like cross-classification (cake vs. dessert).
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 No715154) and by the Catalan government (SGR 2017 1575).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher ACL (Association for Computational Linguistics)
dc.relation.ispartof Calzolari N, Béchet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors. Proceedings of the 12th Language Resources and Evaluation Conference; 2020 May 13-15; Marseilles, France. Stroudsburg (PA): ACL; 2020. p. 5792-801
dc.rights © ACL, Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.title Object naming in language and vision: a survey and a new dataset
dc.type info:eu-repo/semantics/conferenceObject
dc.subject.keyword Object naming
dc.subject.keyword Language and vision
dc.subject.keyword Computer vision
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/715154
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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