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Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition

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Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition

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dc.contributor.author Villegas, Mauricio es_ES
dc.contributor.author Toselli, Alejandro Héctor es_ES
dc.contributor.author Romero Gómez, Verónica es_ES
dc.contributor.author Vidal, Enrique es_ES
dc.date.accessioned 2017-09-20T10:48:57Z
dc.date.available 2017-09-20T10:48:57Z
dc.date.issued 2016
dc.identifier.isbn 978-1-5090-0981-7
dc.identifier.issn 2167-6445
dc.identifier.uri http://hdl.handle.net/10251/87627
dc.description © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. es_ES
dc.description.abstract [EN] Existing transcripts for historic manuscripts are a very valuable resource for training models useful for automatic recognition, aided transcription, and/or indexing of the remaining untranscribed parts of these collections. However, these existing transcripts generally exhibit two main problems which hinder their convenience: a) text of the transcripts is seldom aligned with manuscript lines, and b) text often deviate very significantly from what can be seen in the manuscript, either because writing style has been modernized or abbreviations have been expanded, or both. This work presents an analysis of these problems and discusses possible solutions for minimizing human effort needed to adapt existing transcripts in order to render them usable. Empirical results presented show the huge performance gain that can be obtained by adequately adapting the transcripts, thus motivating future development of the proposed solutions. es_ES
dc.description.sponsorship We are very grateful to Carlos Lechner and Celio Hernández who helped in the creation of the ground truth of the Alcaraz dataset. This work has been partially supported by the European Union (EU) Horizon 2020 grant READ (Recognition and Enrichment of Archival Documents) (Ref: 674943), EU project HIMANIS (JPICH programme, Spanish grant Ref: PCIN-2015-068) and MINECO/FEDER, UE under project TIN2015-70924-C2-1-R.
dc.format.extent 6 es_ES
dc.language Inglés es_ES
dc.publisher IEEE es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Handwritten Text Recognition es_ES
dc.subject Historical Manuscripts es_ES
dc.subject Modernized Transcripts es_ES
dc.subject Transcript-image Alignment es_ES
dc.subject Diplomatization es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1109/ICFHR.2016.22
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//PCIN-2015-068/ES/INDEXACION DE MANUSCRITOS HISTORICOS PARA BUSQUEDAS CONTROLADAS POR EL USUARIO/
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-70924-C2-1-R/ES/CONTEXTO, MULTIMODALIDAD Y COLABORACION DEL USUARIO EN PROCESADO DE TEXTO MANUSCRITO/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Villegas, M.; Toselli, AH.; Romero Gómez, V.; Vidal, E. (2016). Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition. IEEE. https://doi.org/10.1109/ICFHR.2016.22 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 15th International Conference on Frontiers in Handwriting Recognition (ICFHR 2016) es_ES
dc.relation.conferencedate October, 23-26, 2016 es_ES
dc.relation.conferenceplace Shenzhen, China es_ES
dc.relation.publisherversion https://doi.org/10.1109/ICFHR.2016.0025 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 321424 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad
dc.contributor.funder European Commission


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