5. A method of detecting emotions, comprising: providing a first feature class and a second feature class of features of a speech input, wherein said first feature class comprises prosodic features and corresponds to a first dimension of an emotional space, and wherein said second feature class comprises voice quality features and corresponds to a second dimension of said emotional space, wherein the first feature class does not include features of the second feature class and the second feature class does not include features of the first feature class; using for said first and second feature classes specialized classifier systems including a first and second classifier, respectively, wherein said first and second classifiers are configured to classify features of said first and second feature classes, respectively, said second classifier includes a plurality of single classifiers, said first classifier and said second classifier operating independently from one another, and each of the specialized classifier systems uses as input only features of a respectively assigned feature class; and combining outputs of said first and second classifiers to form a global classifier configured to output a current emotional state.
5. A method of detecting emotions, comprising: providing a first feature class and a second feature class of features of a speech input, wherein said first feature class comprises prosodic features and corresponds to a first dimension of an emotional space, and wherein said second feature class comprises voice quality features and corresponds to a second dimension of said emotional space, wherein the first feature class does not include features of the second feature class and the second feature class does not include features of the first feature class; using for said first and second feature classes specialized classifier systems including a first and second classifier, respectively, wherein said first and second classifiers are configured to classify features of said first and second feature classes, respectively, said second classifier includes a plurality of single classifiers, said first classifier and said second classifier operating independently from one another, and each of the specialized classifier systems uses as input only features of a respectively assigned feature class; and combining outputs of said first and second classifiers to form a global classifier configured to output a current emotional state. 10. The method according to claim 5 , wherein the second classifier classifies features of the second feature class based at least in part on speaker dependencies.