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.
Index Terms—SVM, ANN, speech emotion recognition, feature reduction.
Xianxin Ke, Yujiao Zhu, Lei Wen, and Wenzhen Zhang are with School of Mechatronic Engineering and Automation, Shanghai University, China (e-mail: email@example.com, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org)
Cite: Xianxin Ke, Yujiao Zhu, Lei Wen, and Wenzhen Zhang, "Speech Emotion Recognition Based on SVM and ANN," International Journal of Machine Learning and Computing vol. 8, no. 3, pp. 198-202, 2018.