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Quevedo: Annotation and processing of graphical languages

dc.conference.date20-25 Jun 2022
dc.conference.placeMarsella
dc.conference.title13th Conference on Language Resources and Evaluation (LREC 2022)
dc.contributor.authorGarcía Sevilla, Antonio Fernando
dc.contributor.authorDíaz Esteban, Alberto
dc.contributor.authorLahoz Bengoechea, José María
dc.date.accessioned2024-10-03T13:47:26Z
dc.date.available2024-10-03T13:47:26Z
dc.date.issued2022-06-25
dc.description.abstractIn this article, we present Quevedo, a software tool we have developed for the task of automatic processing of graphical languages. These are languages which use images to convey meaning, relying not only on the shape of symbols but also on their spatial arrangement in the page, and relative to each other. When presented in image form, these languages require specialized computational processing which is not the same as usually done either for natural language processing or for artificial vision. Quevedo enables this specialized processing, focusing on a data-based approach. As a command line application and library, it provides features for the collection and management of image datasets, and their machine learning recognition using neural networks and recognizer pipelines. This processing requires careful annotation of the source data, for which Quevedo offers an extensive and visual web-based annotation interface. In this article, we also briefly present a case study centered on the task of SignWriting recognition, the original motivation for writing the software. Quevedo is written in Python, and distributed freely under the Open Software License version 3.0.
dc.description.departmentDepto. de Ingeniería de Software e Inteligencia Artificial (ISIA)
dc.description.departmentDepto. de Lengua Española y Teoría de la Literatura
dc.description.facultyFac. de Informática
dc.description.facultyFac. de Filología
dc.description.refereedTRUE
dc.description.sponsorshipIndra
dc.description.sponsorshipFundación Universia
dc.description.sponsorshipFundación BBVA
dc.description.statuspub
dc.identifier.citationSevilla, A. F. G., Díaz Esteban, A., & Lahoz-Bengoechea, J. M. (2022). Quevedo: Annotation and processing of graphical languages. En Proceedings of the 13th Conference on Language Resources and Evaluation (LREC2022) (pp. 2528-2535). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.269.pdf
dc.identifier.officialurlhttp://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.269.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.14352/108619
dc.language.isoeng
dc.page.final2535
dc.page.initial2528
dc.relation.projectIDinfo:eu-repo/grantAgreement/Indra y Fundación Universia/Ayudas a proyectos de investigación en Tecnologías Accesibles/PR2014_19/01//Visualizando la SignoEscritura/VisSE
dc.relation.projectIDinfo:eu-repo/grantAgreement/Fundación BBVA/Beca Leonardo a Investigadores y Creadores Culturales/IN[21]_HMS_LIN_0070//Signario de LSE: Diccionario paramétrico de la lengua de signos española/
dc.rightsAttribution-NonCommercial 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subject.keywordGraphical languages
dc.subject.keywordAnnotation
dc.subject.keywordDatasets
dc.subject.keywordMachine learning
dc.subject.keywordOpen software
dc.subject.ucmBases de datos (Informática)
dc.subject.ucmSoftware
dc.subject.ucmInteligencia artificial (Informática)
dc.subject.ucmSistemas expertos
dc.subject.ucmLingüística
dc.subject.unesco1203.12 Bancos de Datos
dc.subject.unesco1203.04 Inteligencia Artificial
dc.subject.unesco5701 Lingüística Aplicada
dc.subject.unesco5701.04 Lingüística Informatizada
dc.subject.unesco5705.06 Fonología
dc.titleQuevedo: Annotation and processing of graphical languages
dc.typeconference paper
dc.type.hasVersionVoR
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoveryb0a639f9-8768-4af7-be19-19194a01f3fe

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