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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2018 Vol.8(3): 198-202 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.3.687

Speech Emotion Recognition Based on SVM and ANN

Xianxin Ke, Yujiao Zhu, Lei Wen, and Wenzhen Zhang
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: xxke@staff.shu.edu.cn, 1449803020@qq.com, 405969292@qq.com, 1299896265@qq.com)

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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.

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