ANN application in emotional speech analysis
by Jana Tuckova; Martin Sramka
International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 4, No. 3, 2012

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.

Online publication date: Sat, 06-Sep-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Analysis Techniques and Strategies (IJDATS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com