Multi-objective optimisation of wavelet features for phoneme recognition

Autores
Vignolo, Leandro; Rufiner, Hugo Leonardo; Milone, Diego H.
Año de publicación
2016
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
We proposed a novel approach for the optimisation of over-complete decompositions from a WPT dictionary based on a multi-objective genetic algorithm (MOGA). The MOGA allows to maximise the classification accuracy while minimising the number of features. For the purpose of obtaining appropriate features for state of the art speech recognizers, a classifier based on hidden Markov models (HMM) is used to estimate the capability of candidate solutions, using on a set of English phonemes.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/57025
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/57025
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Multi-objective optimisation of wavelet features for phoneme recognitionVignolo, LeandroRufiner, Hugo LeonardoMilone, Diego H.Ciencias InformáticasWe proposed a novel approach for the optimisation of over-complete decompositions from a WPT dictionary based on a multi-objective genetic algorithm (MOGA). The MOGA allows to maximise the classification accuracy while minimising the number of features. For the purpose of obtaining appropriate features for state of the art speech recognizers, a classifier based on hidden Markov models (HMM) is used to estimate the capability of candidate solutions, using on a set of English phonemes.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2016-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf131-133http://sedici.unlp.edu.ar/handle/10915/57025enginfo:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/ASAI-20_0.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:06:13Zoai:sedici.unlp.edu.ar:10915/57025Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:06:13.316SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Multi-objective optimisation of wavelet features for phoneme recognition
title Multi-objective optimisation of wavelet features for phoneme recognition
spellingShingle Multi-objective optimisation of wavelet features for phoneme recognition
Vignolo, Leandro
Ciencias Informáticas
title_short Multi-objective optimisation of wavelet features for phoneme recognition
title_full Multi-objective optimisation of wavelet features for phoneme recognition
title_fullStr Multi-objective optimisation of wavelet features for phoneme recognition
title_full_unstemmed Multi-objective optimisation of wavelet features for phoneme recognition
title_sort Multi-objective optimisation of wavelet features for phoneme recognition
dc.creator.none.fl_str_mv Vignolo, Leandro
Rufiner, Hugo Leonardo
Milone, Diego H.
author Vignolo, Leandro
author_facet Vignolo, Leandro
Rufiner, Hugo Leonardo
Milone, Diego H.
author_role author
author2 Rufiner, Hugo Leonardo
Milone, Diego H.
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
topic Ciencias Informáticas
dc.description.none.fl_txt_mv We proposed a novel approach for the optimisation of over-complete decompositions from a WPT dictionary based on a multi-objective genetic algorithm (MOGA). The MOGA allows to maximise the classification accuracy while minimising the number of features. For the purpose of obtaining appropriate features for state of the art speech recognizers, a classifier based on hidden Markov models (HMM) is used to estimate the capability of candidate solutions, using on a set of English phonemes.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description We proposed a novel approach for the optimisation of over-complete decompositions from a WPT dictionary based on a multi-objective genetic algorithm (MOGA). The MOGA allows to maximise the classification accuracy while minimising the number of features. For the purpose of obtaining appropriate features for state of the art speech recognizers, a classifier based on hidden Markov models (HMM) is used to estimate the capability of candidate solutions, using on a set of English phonemes.
publishDate 2016
dc.date.none.fl_str_mv 2016-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/57025
url http://sedici.unlp.edu.ar/handle/10915/57025
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/ASAI-20_0.pdf
info:eu-repo/semantics/altIdentifier/issn/2451-7585
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
dc.format.none.fl_str_mv application/pdf
131-133
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.070432

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