Acoustic feature selection and classification of emotions in speech using a 3D continuous emotion model
In this paper we report the results obtained from experiments with a database of emotional speech in English in order to find the most important acoustic features to estimate Emotion Primitives which determine the emotional content on speech. We are interested in exploiting the potential benefits of c...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2012 |
| País: | México |
| Institución: | Instituto Nacional de Astrofísica, Óptica y Electrónica |
| Repositorio: | Repositorio Institucional del INAOE |
| Idioma: | inglés |
| OAI Identifier: | oai:inaoe.repositorioinstitucional.mx:1009/1956 |
| Acceso en línea: | http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1956 |
| Access Level: | acceso abierto |
| Palabra clave: | info:eu-repo/classification/Automatic emotion recognition/Automatic emotion recognition info:eu-repo/classification/Continuous emotion model/Continuous emotion model info:eu-repo/classification/Feature selection/Feature selection info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/12 info:eu-repo/classification/cti/1203 |
| Sumario: | In this paper we report the results obtained from experiments with a database of emotional speech in English in order to find the most important acoustic features to estimate Emotion Primitives which determine the emotional content on speech. We are interested in exploiting the potential benefits of continuous emotion models, so in this paper we demonstrate the feasibility of applying this approach to annotation of emotional speech and we explore ways to take advantage of this kind of annotation to improve the automatic classification of basic emotions. |
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