Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech
ABSTRACT: This paper proposes the application of measures based on nonlinear dynamics for emotional speech characterization. Measures such as mutual information, dimension correlation, entropy correlation, Shannon’s entropy, Lempel–Ziv complexity and Hurst exponent are extracted from the samples of...
- Autores:
-
Orozco Arroyave, Juan Rafael
Henríquez Rodríguez, Patricia
Alonso Hernández, Jesús Bernardino
Ferrer Ballester, Miguel Ángel
Travieso González, Carlos Manuel
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2013
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/35812
- Acceso en línea:
- https://hdl.handle.net/10495/35812
- Palabra clave:
- Nonlinear Dynamics
Dinámicas no Lineales
Expressed Emotion
Emoción Expresada
Expressed Emotion
Neural networks
Redes de neuronas
http://aims.fao.org/aos/agrovoc/c_37467
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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| dc.title.spa.fl_str_mv |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| title |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| spellingShingle |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech Nonlinear Dynamics Dinámicas no Lineales Expressed Emotion Emoción Expresada Expressed Emotion Neural networks Redes de neuronas http://aims.fao.org/aos/agrovoc/c_37467 |
| title_short |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| title_full |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| title_fullStr |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| title_full_unstemmed |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| title_sort |
Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech |
| dc.creator.fl_str_mv |
Orozco Arroyave, Juan Rafael Henríquez Rodríguez, Patricia Alonso Hernández, Jesús Bernardino Ferrer Ballester, Miguel Ángel Travieso González, Carlos Manuel |
| dc.contributor.author.none.fl_str_mv |
Orozco Arroyave, Juan Rafael Henríquez Rodríguez, Patricia Alonso Hernández, Jesús Bernardino Ferrer Ballester, Miguel Ángel Travieso González, Carlos Manuel |
| dc.contributor.researchgroup.spa.fl_str_mv |
Grupo de Investigación en Telecomunicaciones Aplicadas (GITA) |
| dc.subject.decs.none.fl_str_mv |
Nonlinear Dynamics Dinámicas no Lineales Expressed Emotion Emoción Expresada Expressed Emotion |
| topic |
Nonlinear Dynamics Dinámicas no Lineales Expressed Emotion Emoción Expresada Expressed Emotion Neural networks Redes de neuronas http://aims.fao.org/aos/agrovoc/c_37467 |
| dc.subject.agrovoc.none.fl_str_mv |
Neural networks Redes de neuronas |
| dc.subject.agrovocuri.none.fl_str_mv |
http://aims.fao.org/aos/agrovoc/c_37467 |
| description |
ABSTRACT: This paper proposes the application of measures based on nonlinear dynamics for emotional speech characterization. Measures such as mutual information, dimension correlation, entropy correlation, Shannon’s entropy, Lempel–Ziv complexity and Hurst exponent are extracted from the samples of a database of emotional speech. Then, summary statistics such as mean, standard deviation, skewness and kurtosis are applied on the extracted measures. Experiments were conducted on the Berlin emotional speech database for a three-class problem (neutral, fear and anger as emotional states). Feature selection is accomplished and a methodology is proposed to find the best features. In order to evaluate the discrimination ability of the selected features, a neural network classifier is used. The global success rate is 93.78 ± 3.18 %. |
| publishDate |
2013 |
| dc.date.issued.none.fl_str_mv |
2013 |
| dc.date.accessioned.none.fl_str_mv |
2023-07-08T01:43:51Z |
| dc.date.available.none.fl_str_mv |
2023-07-08T01:43:51Z |
| dc.type.spa.fl_str_mv |
Artículo de investigación |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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https://purl.org/redcol/resource_type/ART |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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P. Henríquez Rodríguez, J. B. Alonso Hernández, M. A. Ferrer Ballester, C. M. Travieso González, and J. R. Orozco-Arroyave, “Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech,” Cognit. Comput., vol. 5, no. 4, pp. 517–525, 2013, doi: 10.1007/s12559-012-9157-0. |
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1866-9956 |
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https://hdl.handle.net/10495/35812 |
| dc.identifier.doi.none.fl_str_mv |
10.1007/s12559-012-9157-0 |
| dc.identifier.eissn.none.fl_str_mv |
1866-9964 |
| identifier_str_mv |
P. Henríquez Rodríguez, J. B. Alonso Hernández, M. A. Ferrer Ballester, C. M. Travieso González, and J. R. Orozco-Arroyave, “Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech,” Cognit. Comput., vol. 5, no. 4, pp. 517–525, 2013, doi: 10.1007/s12559-012-9157-0. 1866-9956 10.1007/s12559-012-9157-0 1866-9964 |
| url |
https://hdl.handle.net/10495/35812 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartofjournalabbrev.spa.fl_str_mv |
Cognit. Comput. |
| dc.relation.citationendpage.spa.fl_str_mv |
525 |
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517 |
| dc.relation.citationvolume.spa.fl_str_mv |
5 |
| dc.relation.ispartofjournal.spa.fl_str_mv |
Cognitive Computation |
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http://creativecommons.org/licenses/by-nc-nd/2.5/co/ |
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https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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openAccess |
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Springer |
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Nueva York, Estados Unidos |
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Orozco Arroyave, Juan RafaelHenríquez Rodríguez, PatriciaAlonso Hernández, Jesús BernardinoFerrer Ballester, Miguel ÁngelTravieso González, Carlos ManuelGrupo de Investigación en Telecomunicaciones Aplicadas (GITA)2023-07-08T01:43:51Z2023-07-08T01:43:51Z2013P. Henríquez Rodríguez, J. B. Alonso Hernández, M. A. Ferrer Ballester, C. M. Travieso González, and J. R. Orozco-Arroyave, “Global Selection of Features for Nonlinear Dynamics Characterization of Emotional Speech,” Cognit. Comput., vol. 5, no. 4, pp. 517–525, 2013, doi: 10.1007/s12559-012-9157-0.1866-9956https://hdl.handle.net/10495/3581210.1007/s12559-012-9157-01866-9964ABSTRACT: This paper proposes the application of measures based on nonlinear dynamics for emotional speech characterization. Measures such as mutual information, dimension correlation, entropy correlation, Shannon’s entropy, Lempel–Ziv complexity and Hurst exponent are extracted from the samples of a database of emotional speech. Then, summary statistics such as mean, standard deviation, skewness and kurtosis are applied on the extracted measures. Experiments were conducted on the Berlin emotional speech database for a three-class problem (neutral, fear and anger as emotional states). Feature selection is accomplished and a methodology is proposed to find the best features. In order to evaluate the discrimination ability of the selected features, a neural network classifier is used. The global success rate is 93.78 ± 3.18 %.COL00444489application/pdfengSpringerNueva York, Estados Unidoshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Global Selection of Features for Nonlinear Dynamics Characterization of Emotional SpeechArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionNonlinear DynamicsDinámicas no LinealesExpressed EmotionEmoción ExpresadaExpressed EmotionNeural networksRedes de neuronashttp://aims.fao.org/aos/agrovoc/c_37467Cognit. 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