A Methodology to Measure the Diachronic Language Distance between Three Languages Based on Perplexity
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías da Información | gl |
| dc.contributor.affiliation | Universidade de Santiago de Compostela. Departamento de Lingua e Literatura Españolas, Teoría da Literatura e Lingüística Xeral | gl |
| dc.contributor.area | Área de Enxeñaría e Arquitectura | |
| dc.contributor.author | Pichel Campos, José Ramom | |
| dc.contributor.author | Gamallo Otero, Pablo | |
| dc.contributor.author | Alegría, Iñaki | |
| dc.contributor.author | Neves, Marco | |
| dc.date.accessioned | 2021-03-05T12:17:30Z | |
| dc.date.available | 2021-09-01T01:00:08Z | |
| dc.date.issued | 2020 | |
| dc.description | This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Quantitative Linguistics on 01 Mar 2020, available online: http://www.tandfonline.com/10.1080/09296174.2020.1732177 | gl |
| dc.description.abstract | The aim of this paper is to apply a corpus-based methodology, based on the measure of perplexity, to automatically calculate the cross-lingual language distance between historical periods of three languages. The three historical corpora have been constructed and collected with the closest spelling to the original on a balanced basis of fiction and non-fiction. This methodology has been applied to measure the historical distance of Galician with respect to Portuguese and Spanish, from the Middle Ages to the end of the 20th century, both in original spelling and automatically transcribed spelling. The quantitative results are contrasted with hypotheses extracted from experts in historical linguistics. Results show that Galician and Portuguese are varieties of the same language in the Middle Ages and that Galician converges and diverges with Portuguese and Spanish since the last period of the 19th century. In this process, orthography plays a relevant role. It should be pointed out that the method is unsupervised and can be applied to other languages | gl |
| dc.description.peerreviewed | SI | gl |
| dc.description.sponsorship | This work has received financial support from DOMINO project [PGC2018-102041-B-I00, MCIU/AEI/FEDER, UE]; eRisk project [RTI2018-093336-B-C21]; the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2016-2019, ED431G/08, Consolidation and structuring of Groups with Growth Potential: 745ED431B 2017/39) and the European Regional Development Fund (ERDF) | gl |
| dc.identifier.citation | José Ramom Pichel, Pablo Gamallo, Iñaki Alegria & Marco Neves (2020) A Methodology to Measure the Diachronic Language Distance between Three Languages Based on Perplexity, Journal of Quantitative Linguistics, DOI: 10.1080/09296174.2020.1732177 | gl |
| dc.identifier.doi | 10.1080/09296174.2020.1732177 | |
| dc.identifier.essn | 1744-5035 | |
| dc.identifier.issn | 0929-6174 | |
| dc.identifier.uri | http://hdl.handle.net/10347/24655 | |
| dc.language.iso | eng | gl |
| dc.publisher | Taylor & Francis | gl |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093336-B-C21/ES/TECNOLOGIAS PARA LA PREDICCION TEMPRANA DE SIGNOS RELACIONADOS CON TRASTORNOS PSICOLOGICOS | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-102041-B-I00/ES/TRADUCCION AUTOMATICA NEURONAL, EN DOMINIO, NO SUPERVISADA | |
| dc.relation.publisherversion | https://doi.org/10.1080/09296174.2020.1732177 | gl |
| dc.rights | © Taylor & Francis, 2020 | gl |
| dc.rights.accessRights | open access | gl |
| dc.title | A Methodology to Measure the Diachronic Language Distance between Three Languages Based on Perplexity | gl |
| dc.type | journal article | gl |
| dc.type.hasVersion | AM | gl |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 898ee1bb-f9e8-4a75-9858-a6c9142bc99e | |
| relation.isAuthorOfPublication.latestForDiscovery | 898ee1bb-f9e8-4a75-9858-a6c9142bc99e |
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