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Language technology for handwritten text recognition

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Language technology for handwritten text recognition

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Nombre: Toselli;Serrano;G ...
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dc.contributor.author Toselli, Alejandro Héctor es_ES
dc.contributor.author Serrano Martínez-Santos, Nicolás es_ES
dc.contributor.author Giménez Pastor, Adrián es_ES
dc.contributor.author Khoury, Ihab es_ES
dc.contributor.author Juan Císcar, Alfonso es_ES
dc.contributor.author Vidal Ruiz, Enrique es_ES
dc.date.accessioned 2014-03-13T07:49:10Z
dc.date.issued 2012
dc.identifier.isbn 978-3-642-35291-1
dc.identifier.issn 1865-0929
dc.identifier.uri http://hdl.handle.net/10251/36452
dc.description.abstract This paper shows how the nowadays prevalent technology used in HTR borrows concepts and methods from the field of ASR; i.e. those based on Hidden Markov Models (HMMs). Additionally, it will be described a HTR approach based on employing Bernoulli distributions rather than Gaussian-Mixture distributions for the HMM-state emission probability of observations. Finally, handwritten text recognition evaluation results are reported for several corpora involving different characteristics and languages. es_ES
dc.description.sponsorship Work supported by the EC (FEDER), the Spanish MEC under the MIPRCV “Consolider Ingenio 2010” research programme (CSD2007- 00018) and the Spanisg Government (MICINN and “Plan E”) under the MITTRAL (TIN2009-14633-C03-01) research project.
dc.format.extent 9 es_ES
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Advances in Speech and Language Technologies for Iberian Languages es_ES
dc.relation.ispartofseries Communications in Computer and Information Science;328
dc.rights Reserva de todos los derechos es_ES
dc.subject Mixture of Gaussian Densities es_ES
dc.subject Mixture of Bernoulli Distributions es_ES
dc.subject Hidden Markov Model Emission Probability es_ES
dc.subject On-Line Continuous Handwritten Text Recognition es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Language technology for handwritten text recognition es_ES
dc.type Capítulo de libro es_ES
dc.embargo.lift 10000-01-01
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1007/978-3-642-35292-8_19
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CSD2007-00018/ES/Multimodal Intraction in Pattern Recognition and Computer Visionm/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2009-14633-C03-01/ES/Multimodal Interaction For Text Transcription With Adaptive Learning/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario Mixto Tecnológico de Informática - Institut Universitari Mixt Tecnològic d'Informàtica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Toselli, AH.; Serrano Martínez-Santos, N.; Giménez Pastor, A.; Khoury, I.; Juan Císcar, A.; Vidal Ruiz, E. (2012). Language technology for handwritten text recognition. En Advances in Speech and Language Technologies for Iberian Languages. Springer Verlag (Germany). 328:178-186. https://doi.org/10.1007/978-3-642-35292-8_19 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename IberSPEECH 2012 Conference es_ES
dc.relation.conferencedate November 21-23, 2012 es_ES
dc.relation.conferenceplace Madrid es_ES
dc.relation.publisherversion http://link.springer.com/chapter/10.1007%2F978-3-642-35292-8_19 es_ES
dc.description.upvformatpinicio 178 es_ES
dc.description.upvformatpfin 186 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 328 es_ES
dc.relation.senia 243101
dc.contributor.funder European Regional Development Fund
dc.contributor.funder Ministerio de Ciencia e Innovación
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