Argentine Spanish segmental duration prediction
- Autores
- Torres, H. M.; Gurlekian, J. A.
- Año de publicación
- 2012
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- In this paper we model the segmental duration of Spanish spoken in Buenos Aires, considering its application in a text-to-speech system. The work was performed on two hand labeled databases. We use artificial neural networks as predictor, and all the input features can be extracted automatically from the speech text. We experimented with a neural network for all phonemes and one neural network for phoneme. In both cases the results are very promising for the two databases used. The order of importance of input features revealed to be different for each of the methods tested and different according to the speaker style.
Sociedad Argentina de Informática e Investigación Operativa - Materia
-
Ciencias Informáticas
Phone duration prediction
Prosody prediction
Text-To-Speech - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/123916
Ver los metadatos del registro completo
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Argentine Spanish segmental duration predictionTorres, H. M.Gurlekian, J. A.Ciencias InformáticasPhone duration predictionProsody predictionText-To-SpeechIn this paper we model the segmental duration of Spanish spoken in Buenos Aires, considering its application in a text-to-speech system. The work was performed on two hand labeled databases. We use artificial neural networks as predictor, and all the input features can be extracted automatically from the speech text. We experimented with a neural network for all phonemes and one neural network for phoneme. In both cases the results are very promising for the two databases used. The order of importance of input features revealed to be different for each of the methods tested and different according to the speaker style.Sociedad Argentina de Informática e Investigación Operativa2012-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf156-167http://sedici.unlp.edu.ar/handle/10915/123916enginfo:eu-repo/semantics/altIdentifier/url/https://41jaiio.sadio.org.ar/sites/default/files/14_AST_2012.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2806info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:29:43Zoai:sedici.unlp.edu.ar:10915/123916Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:29:43.455SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Argentine Spanish segmental duration prediction |
title |
Argentine Spanish segmental duration prediction |
spellingShingle |
Argentine Spanish segmental duration prediction Torres, H. M. Ciencias Informáticas Phone duration prediction Prosody prediction Text-To-Speech |
title_short |
Argentine Spanish segmental duration prediction |
title_full |
Argentine Spanish segmental duration prediction |
title_fullStr |
Argentine Spanish segmental duration prediction |
title_full_unstemmed |
Argentine Spanish segmental duration prediction |
title_sort |
Argentine Spanish segmental duration prediction |
dc.creator.none.fl_str_mv |
Torres, H. M. Gurlekian, J. A. |
author |
Torres, H. M. |
author_facet |
Torres, H. M. Gurlekian, J. A. |
author_role |
author |
author2 |
Gurlekian, J. A. |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Phone duration prediction Prosody prediction Text-To-Speech |
topic |
Ciencias Informáticas Phone duration prediction Prosody prediction Text-To-Speech |
dc.description.none.fl_txt_mv |
In this paper we model the segmental duration of Spanish spoken in Buenos Aires, considering its application in a text-to-speech system. The work was performed on two hand labeled databases. We use artificial neural networks as predictor, and all the input features can be extracted automatically from the speech text. We experimented with a neural network for all phonemes and one neural network for phoneme. In both cases the results are very promising for the two databases used. The order of importance of input features revealed to be different for each of the methods tested and different according to the speaker style. Sociedad Argentina de Informática e Investigación Operativa |
description |
In this paper we model the segmental duration of Spanish spoken in Buenos Aires, considering its application in a text-to-speech system. The work was performed on two hand labeled databases. We use artificial neural networks as predictor, and all the input features can be extracted automatically from the speech text. We experimented with a neural network for all phonemes and one neural network for phoneme. In both cases the results are very promising for the two databases used. The order of importance of input features revealed to be different for each of the methods tested and different according to the speaker style. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-08 |
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 |
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conferenceObject |
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http://sedici.unlp.edu.ar/handle/10915/123916 |
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http://sedici.unlp.edu.ar/handle/10915/123916 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 156-167 |
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