Subir material

Suba sus trabajos a SEDICI, para mejorar notoriamente su visibilidad e impacto

 

Mostrar el registro sencillo del ítem

dc.date.accessioned 2021-09-01T13:43:48Z
dc.date.available 2021-09-01T13:43:48Z
dc.date.issued 2012
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/123916
dc.description.abstract 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. en
dc.format.extent 156-167 es
dc.language en es
dc.subject Phone duration prediction es
dc.subject Prosody prediction es
dc.subject Text-To-Speech es
dc.title Argentine Spanish segmental duration prediction en
dc.type Objeto de conferencia es
sedici.identifier.uri https://41jaiio.sadio.org.ar/sites/default/files/14_AST_2012.pdf es
sedici.identifier.issn 1850-2806 es
sedici.creator.person Torres, H. M. es
sedici.creator.person Gurlekian, J. A. es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Sociedad Argentina de Informática e Investigación Operativa es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.date.exposure 2012-08
sedici.relation.event XIII Argentine Symposium on Technology (AST 2012) (XLII JAIIO, La Plata, 27 y 28 de agosto de 2012) es
sedici.description.peerReview peer-review es


Descargar archivos

Thumbnail
Documento_completo
Descargar archivo (777.6Kb) - PDF
Icon
Enlace externo

Este ítem aparece en la(s) siguiente(s) colección(ones)

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)