Explicit length modelling for statistical machine translation

[EN] Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisations for statistical machine translation (SMT) are presented. More prec...

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Detalhes bibliográficos
Autores: Silvestre Cerdà, Joan Albert|||0000-0003-2291-8296, Civera Saiz, Jorge|||0000-0002-0963-0143, Andrés Ferrer, Jesús
Formato: artículo
Fecha de publicación:2012
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/34996
Acesso em linha:https://riunet.upv.es/handle/10251/34996
Access Level:acceso abierto
Palavra-chave:Length modelling
Log-linear models
Phrase-based models
Statistical machine translation
ESTADISTICA E INVESTIGACION OPERATIVA
LENGUAJES Y SISTEMAS INFORMATICOS
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spelling Explicit length modelling for statistical machine translationSilvestre Cerdà, Joan Albert|||0000-0003-2291-8296Civera Saiz, Jorge|||0000-0002-0963-0143Andrés Ferrer, JesúsLength modellingLog-linear modelsPhrase-based modelsStatistical machine translationESTADISTICA E INVESTIGACION OPERATIVALENGUAJES Y SISTEMAS INFORMATICOS[EN] Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisations for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, a systematic evaluation on reference SMT tasks considering different language pairs proves the benefits of explicit length modelling.Work supported by the EC (FEDER/FSE) under the transLectures project (FP7-ICT-2011-7-287755) and the Spanish MEC/MICINN under the MIPRCV "Consolider Ingenio 2010" program (CSD2007-00018) and iTrans2 (TIN2009-14511) projects and FPU grant (AP2010-4349). Also supported by the Spanish MITyC under the erudito.com (TSI-020110-2009-439) project and by the Generalitat Valenciana under grants Prometeo/2009/014 and GV/2010/067, and by the UPV under the AdInTAO (20091027) project. The authors wish to thank the anonymous reviewers for their criticisms and suggestions.ElsevierDepartamento de Sistemas Informáticos y ComputaciónEscuela Politécnica Superior de AlcoyEscuela Técnica Superior de Ingeniería InformáticaInstituto Universitario Valenciano de Investigación en Inteligencia ArtificialEuropean CommissionMinisterio de Ciencia e InnovaciónMinisterio de Industria, Turismo y ComercioGeneralitat ValencianaUniversitat Politècnica de ValènciaMinisterio de EducaciónRepositorio Institucional de la Universitat Politècnica de València Riunet20122012-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/34996reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengEuropean Commission https://doi.org/10.13039/501100000780 FP7 287755 Transcription and Translation of Video LecturesMinisterio de Educación y Ciencia https://doi.org/10.13039/501100008743 CSD2007-00018 Multimodal Intraction in Pattern Recognition and Computer VisionmMinisterio de Educación, Argentina ME AP2010-4349 AP2010-4349Ministerio de Industria, Turismo y Comercio MITURCO TSI-020110-2009-0439 ERUDITO.COMGeneralitat Valenciana https://doi.org/10.13039/501100003359 PROMETEO09%2F2009%2F014 Adaptive learning and multimodality in pattern recognition (Almapater)Universitat Politècnica de València https://doi.org/10.13039/501100004233 20091027Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 TIN2009-14511 Traduccion De Textos Y Transcripcion De Voz InteractivasGeneralitat Valenciana https://doi.org/10.13039/501100003359 GV%2F2010%2F067open accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/349962026-06-13T07:49:27Z
dc.title.none.fl_str_mv Explicit length modelling for statistical machine translation
title Explicit length modelling for statistical machine translation
spellingShingle Explicit length modelling for statistical machine translation
Silvestre Cerdà, Joan Albert|||0000-0003-2291-8296
Length modelling
Log-linear models
Phrase-based models
Statistical machine translation
ESTADISTICA E INVESTIGACION OPERATIVA
LENGUAJES Y SISTEMAS INFORMATICOS
title_short Explicit length modelling for statistical machine translation
title_full Explicit length modelling for statistical machine translation
title_fullStr Explicit length modelling for statistical machine translation
title_full_unstemmed Explicit length modelling for statistical machine translation
title_sort Explicit length modelling for statistical machine translation
dc.creator.none.fl_str_mv Silvestre Cerdà, Joan Albert|||0000-0003-2291-8296
Civera Saiz, Jorge|||0000-0002-0963-0143
Andrés Ferrer, Jesús
author Silvestre Cerdà, Joan Albert|||0000-0003-2291-8296
author_facet Silvestre Cerdà, Joan Albert|||0000-0003-2291-8296
Civera Saiz, Jorge|||0000-0002-0963-0143
Andrés Ferrer, Jesús
author_role author
author2 Civera Saiz, Jorge|||0000-0002-0963-0143
Andrés Ferrer, Jesús
author2_role author
author
dc.contributor.none.fl_str_mv Departamento de Sistemas Informáticos y Computación
Escuela Politécnica Superior de Alcoy
Escuela Técnica Superior de Ingeniería Informática
Instituto Universitario Valenciano de Investigación en Inteligencia Artificial
European Commission
Ministerio de Ciencia e Innovación
Ministerio de Industria, Turismo y Comercio
Generalitat Valenciana
Universitat Politècnica de València
Ministerio de Educación
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Length modelling
Log-linear models
Phrase-based models
Statistical machine translation
ESTADISTICA E INVESTIGACION OPERATIVA
LENGUAJES Y SISTEMAS INFORMATICOS
topic Length modelling
Log-linear models
Phrase-based models
Statistical machine translation
ESTADISTICA E INVESTIGACION OPERATIVA
LENGUAJES Y SISTEMAS INFORMATICOS
description [EN] Explicit length modelling has been previously explored in statistical pattern recognition with successful results. In this paper, two length models along with two parameter estimation methods and two alternative parametrisations for statistical machine translation (SMT) are presented. More precisely, we incorporate explicit bilingual length modelling in a state-of-the-art log-linear SMT system as an additional feature function in order to prove the contribution of length information. Finally, a systematic evaluation on reference SMT tasks considering different language pairs proves the benefits of explicit length modelling.
publishDate 2012
dc.date.none.fl_str_mv 2012
2012-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/34996
url https://riunet.upv.es/handle/10251/34996
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission https://doi.org/10.13039/501100000780 FP7 287755 Transcription and Translation of Video Lectures
Ministerio de Educación y Ciencia https://doi.org/10.13039/501100008743 CSD2007-00018 Multimodal Intraction in Pattern Recognition and Computer Visionm
Ministerio de Educación, Argentina ME AP2010-4349 AP2010-4349
Ministerio de Industria, Turismo y Comercio MITURCO TSI-020110-2009-0439 ERUDITO.COM
Generalitat Valenciana https://doi.org/10.13039/501100003359 PROMETEO09%2F2009%2F014 Adaptive learning and multimodality in pattern recognition (Almapater)
Universitat Politècnica de València https://doi.org/10.13039/501100004233 20091027
Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 TIN2009-14511 Traduccion De Textos Y Transcripcion De Voz Interactivas
Generalitat Valenciana https://doi.org/10.13039/501100003359 GV%2F2010%2F067
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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