Title: ANN application in emotional speech analysis

Authors: Jana Tuckova; Martin Sramka

Addresses: Czech Technical University in Prague, Faculty of Electrical Engineering, Technicka 2, 166 27 Prague 6, Czech Republic. ' Czech Technical University in Prague, Faculty of Electrical Engineering, Technicka 2, 166 27 Prague 6, Czech Republic

Abstract: In the present text, we deal with the problem of classification of speech emotion. Problems of speech processing are addressed through the use of artificial neural networks (ANNs). The results can be used for two research projects - for prosody modelling and for analysis of disordered speech. The first ANN topology discussed is the multilayer neural network (MLNN) with the BPG learning algorithm, while the supervised SOM (SSOM) is the second ANN topology. Our aim is to combine knowledges from phonetics and ANN but also to try to classify speech signals which are described by music theory. Finally, one solution is given for this problem which is supplemented with a proof.

Keywords: emotions; emotion classification; speech analysis; artificial neural network; ANNs; multilayer neural networks; MLNN; self-organising maps; SOM; prosody modelling; musical theory; U-matrix; matrix of changes; emotional speech; disordered speech.

DOI: 10.1504/IJDATS.2012.047819

International Journal of Data Analysis Techniques and Strategies, 2012 Vol.4 No.3, pp.256 - 276

Published online: 06 Sep 2014 *

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