Speech emotion recognition based on SVM and ANN

Abstract

Speech emotion recognition mainly includes emotion feature extraction, feature reduction and speech emotion recognition model. This paper chooses valid emotional features and extracts the statistical values of the emotional features. Speech emotion recognition model are constructed respectively based on SVM and ANN and the recognition effect of feature reduction respectively on two types of models are compared. The experimental results show that, based on emotion features which is extracted by CASIA emotion corpus, feature reduction can improve recognition accuracy and the recognition effect of speech recognition model based on SVM is better than ANN.