Título

Acoustic feature selection and classification of emotions in speech using a 3D continuous emotion model

Autor

Humberto Pérez Espinosa

CARLOS ALBERTO REYES GARCIA

Luis Villaseñor Pineda

Nivel de Acceso

Acceso Abierto

Licencia

http://creativecommons.org/licenses/by-nc-nd/4.0

Materias

Automatic emotion recognition - (AUTOMATIC EMOTION RECOGNITION) Continuous emotion model - (CONTINUOUS EMOTION MODEL) Feature selection - (FEATURE SELECTION) CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA - (CTI) MATEMÁTICAS - (CTI) CIENCIA DE LOS ORDENADORES - (CTI) CIENCIA DE LOS ORDENADORES - (CTI)

Resumen o descripción

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.

Editor

Elsevier Ltd.

Fecha de publicación

2012

Tipo de publicación

Artículo

Versión de la publicación

Versión aceptada

Recurso de información

http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1956

Formato

application/pdf

Idioma

Inglés

Audiencia

Estudiantes

Investigadores

Público en general

Sugerencia de citación

Perez-Espinosa, H., et al., (2012). Acoustic feature selection and classification of emotions in speech using a 3D continuous emotion model, Biomedical Signal Processing and Control, (7): 79–87

Repositorio Orígen

Repositorio Institucional del INAOE

Descargas

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