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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...
A feature reduction system based on Discriminative Common Vector is presented and evaluated in this paper. The validation of this system was made with three databases, first one is DNA markers and the other two are The ORL Database of Face and The Yale Face Database. Moreover, a supervised classification system has been implemented with three different classifiers, achieving the best success rates...
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