Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44042
Title: Application of nonlinear dynamics characterization to emotional speech
Authors: Henriquez, P. 
Alonso Hernández, Jesús Bernardino 
Ferrer Ballester, Miguel Ángel 
Travieso González, Carlos Manuel 
Orozco-Arroyave, Juan R.
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Nonlinear dynamic, emotional speech, feature selection
Issue Date: 2011
Publisher: 0302-9743
Journal: Lecture Notes in Computer Science 
Conference: 5th International Conference on Nonlinear Speech Processing (NOLISP 2011) 
5th International Conference on Nonlinear Speech Processing, NOLISP 2011 
Abstract: This paper proposes the application of nonlinear measures based on nonlinear dynamics for emotional speech characterization. Measures such as mutual information, dimension correlation, entropy correlation, Shannon entropy, Lempel-Ziv complexity and Hurst exponent are extracted from the samples of a database of emotional speech. Then, 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 threeclass problem (neutral, fear and anger emotional states). Feature selection is accomplished to select a reduced number of features. In order to evaluate the discrimination ability of the selected features a neural network classifier is used. A global success rate of 93.78% is obtained.
URI: http://hdl.handle.net/10553/44042
ISBN: 9783642250194
ISSN: 0302-9743
DOI: 10.1007/978-3-642-25020-0_17
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 7015 LNAI, p. 127-136
Appears in Collections:Actas de congresos
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