Learning emotional speech by using Dirichlet Process Mixtures

Abstract

Our aim in this paper is to illustrate the effectiveness of the Dirichlet Process Mixture (DPM) model for emotional speech class density estimation when the number of Gauss mixture components are unknown. The problem is modeled as a two-class classification problem where the classes are anger and-no-anger. Performance of the algorithm is evaluated on the… (More)

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