|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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