Title :
Emotional speech analysis using artificial neural networks
Author :
Tuckova, Jana ; Sramka, Martin
Author_Institution :
Fac. of Electr. Eng., Czech Tech. Univ. in Prague, Prague, 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 (ANN). The results can be use 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) are the second ANN topology. Our aim is to verify the various of knowledge from phonetics and ANN but also to try to classify speech signals which are described by musical theory. Finally, one solution is given for this problem which is supplemented with a proof.
Keywords :
backpropagation; neural nets; speech processing; ANN topology; BPG learning algorithm; artificial neural network; disordered speech; emotional speech analysis; multilayer neural network; musical theory; phonetics; prosody modelling; speech emotion; speech processing; speech signal classification; supervised SOM; Artificial neural networks; Databases; Frequency domain analysis; Neurons; Speech; Speech processing; Training;
Conference_Titel :
Computer Science and Information Technology (IMCSIT), Proceedings of the 2010 International Multiconference on
Conference_Location :
Wisla
Print_ISBN :
978-1-4244-6432-6
DOI :
10.1109/IMCSIT.2010.5679941