Beschreibung
Speech emotion recognition is a very important speech technology. an extensive research is made by using different speech information and signal for human emotion recognition. We develop a speech-based emotion classification method using SVM by using standard EMA database. In order to achieve a high emotion classification accuracy we have used SVM with kernel functions, From result obtained by using different kernels functions. From result we conclude that RBF Kernel function in which we got 94.96%, 96.02%, 98.96%, 98.76% accuracy results for Angry, Happy, Neutral, Sad emotions respectively using energy, formant and MFCC features. Our result shows that classification accuracy will be improve using kernel functions.
Autorenporträt
Ms. R. D. Shah is a Post-Graduate Student in Electronics & Communication Engg.(CSE) & Dr. Anilkumar C. Suthar is a Guide and Director of LJIET.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
