Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice
- Autores
- Restrepo Rinckoar, Juan Felipe; Schlotthauer, Gaston
- Año de publicación
- 2018
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Nonlinear measures such as the correlation dimension, the correlation entropy, and the noise level were used in this article to characterize normal and pathological voices. These invariants were estimated through an automated algorithm based on the recently proposed U-correlation integral. Our results show that the voice dynamics have a low dimension. The value of correlation dimension is greater for pathological voices than for normal ones. Furthermore, its value also increases along with the type of the voice. The low correlation entropy values obtained for normal and pathological type 1 and type 2 voices suggest that their dynamics are nearly periodic. Regarding the noise level, in the context of voice signals, it can be interpreted as the power of an additive stochastic perturbation intrinsic to the voice production system. Our estimations suggest that the noise level is greater for pathological voices than for normal ones. Moreover, it increases along with the type of voice, being the highest for type voices. From these results, we can conclude that the voice production dynamical system is more complex in the presence of a pathology. In addition, the presence of the inherent stochastic perturbation strengthens along with the voice type. Finally, based on our results, we propose that the noise level can be used to quantitatively differentiate between type and type voices.
Fil: Restrepo Rinckoar, Juan Felipe. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina - Materia
-
Correlation integral
Correlation entropy
Correlation dimension
Pathological voices - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/96538
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Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human VoiceRestrepo Rinckoar, Juan FelipeSchlotthauer, GastonCorrelation integralCorrelation entropyCorrelation dimensionPathological voiceshttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Nonlinear measures such as the correlation dimension, the correlation entropy, and the noise level were used in this article to characterize normal and pathological voices. These invariants were estimated through an automated algorithm based on the recently proposed U-correlation integral. Our results show that the voice dynamics have a low dimension. The value of correlation dimension is greater for pathological voices than for normal ones. Furthermore, its value also increases along with the type of the voice. The low correlation entropy values obtained for normal and pathological type 1 and type 2 voices suggest that their dynamics are nearly periodic. Regarding the noise level, in the context of voice signals, it can be interpreted as the power of an additive stochastic perturbation intrinsic to the voice production system. Our estimations suggest that the noise level is greater for pathological voices than for normal ones. Moreover, it increases along with the type of voice, being the highest for type voices. From these results, we can conclude that the voice production dynamical system is more complex in the presence of a pathology. In addition, the presence of the inherent stochastic perturbation strengthens along with the voice type. Finally, based on our results, we propose that the noise level can be used to quantitatively differentiate between type and type voices.Fil: Restrepo Rinckoar, Juan Felipe. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; ArgentinaJohn Wiley & Sons Inc2018-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/96538Restrepo Rinckoar, Juan Felipe; Schlotthauer, Gaston; Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice; John Wiley & Sons Inc; Complexity; 2018; 4-2018; 1-91076-2787CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.hindawi.com/journals/complexity/2018/2173640/info:eu-repo/semantics/altIdentifier/doi/10.1155/2018/2173640info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:37:37Zoai:ri.conicet.gov.ar:11336/96538instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:37:38.16CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
title |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
spellingShingle |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice Restrepo Rinckoar, Juan Felipe Correlation integral Correlation entropy Correlation dimension Pathological voices |
title_short |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
title_full |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
title_fullStr |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
title_full_unstemmed |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
title_sort |
Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice |
dc.creator.none.fl_str_mv |
Restrepo Rinckoar, Juan Felipe Schlotthauer, Gaston |
author |
Restrepo Rinckoar, Juan Felipe |
author_facet |
Restrepo Rinckoar, Juan Felipe Schlotthauer, Gaston |
author_role |
author |
author2 |
Schlotthauer, Gaston |
author2_role |
author |
dc.subject.none.fl_str_mv |
Correlation integral Correlation entropy Correlation dimension Pathological voices |
topic |
Correlation integral Correlation entropy Correlation dimension Pathological voices |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/2.2 https://purl.org/becyt/ford/2 |
dc.description.none.fl_txt_mv |
Nonlinear measures such as the correlation dimension, the correlation entropy, and the noise level were used in this article to characterize normal and pathological voices. These invariants were estimated through an automated algorithm based on the recently proposed U-correlation integral. Our results show that the voice dynamics have a low dimension. The value of correlation dimension is greater for pathological voices than for normal ones. Furthermore, its value also increases along with the type of the voice. The low correlation entropy values obtained for normal and pathological type 1 and type 2 voices suggest that their dynamics are nearly periodic. Regarding the noise level, in the context of voice signals, it can be interpreted as the power of an additive stochastic perturbation intrinsic to the voice production system. Our estimations suggest that the noise level is greater for pathological voices than for normal ones. Moreover, it increases along with the type of voice, being the highest for type voices. From these results, we can conclude that the voice production dynamical system is more complex in the presence of a pathology. In addition, the presence of the inherent stochastic perturbation strengthens along with the voice type. Finally, based on our results, we propose that the noise level can be used to quantitatively differentiate between type and type voices. Fil: Restrepo Rinckoar, Juan Felipe. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Investigación y Desarrollo En Bioingeniería y Bioinformática; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina |
description |
Nonlinear measures such as the correlation dimension, the correlation entropy, and the noise level were used in this article to characterize normal and pathological voices. These invariants were estimated through an automated algorithm based on the recently proposed U-correlation integral. Our results show that the voice dynamics have a low dimension. The value of correlation dimension is greater for pathological voices than for normal ones. Furthermore, its value also increases along with the type of the voice. The low correlation entropy values obtained for normal and pathological type 1 and type 2 voices suggest that their dynamics are nearly periodic. Regarding the noise level, in the context of voice signals, it can be interpreted as the power of an additive stochastic perturbation intrinsic to the voice production system. Our estimations suggest that the noise level is greater for pathological voices than for normal ones. Moreover, it increases along with the type of voice, being the highest for type voices. From these results, we can conclude that the voice production dynamical system is more complex in the presence of a pathology. In addition, the presence of the inherent stochastic perturbation strengthens along with the voice type. Finally, based on our results, we propose that the noise level can be used to quantitatively differentiate between type and type voices. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-04 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/96538 Restrepo Rinckoar, Juan Felipe; Schlotthauer, Gaston; Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice; John Wiley & Sons Inc; Complexity; 2018; 4-2018; 1-9 1076-2787 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/96538 |
identifier_str_mv |
Restrepo Rinckoar, Juan Felipe; Schlotthauer, Gaston; Invariant Measures Based on the U-Correlation Integral: An Application to the Study of Human Voice; John Wiley & Sons Inc; Complexity; 2018; 4-2018; 1-9 1076-2787 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://www.hindawi.com/journals/complexity/2018/2173640/ info:eu-repo/semantics/altIdentifier/doi/10.1155/2018/2173640 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
John Wiley & Sons Inc |
publisher.none.fl_str_mv |
John Wiley & Sons Inc |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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13.22299 |