ANN application in emotional speech analysis

Jana Tuckova and Martin Sramka

International Journal of Data Analysis Techniques and Strategies, 2012, vol. 4, issue 3, 256-276

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. (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ids:injdan:v:4:y:2012:i:3:p:256-276

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