A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM

作者：Huang Chenchen^*; Gong Wei; Fu Wenlong; Feng Dongyu

来源：Mathematical Problems in Engineering, 2014, 2014: 749604.

DOI：10.1155/2014/749604

Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically. By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature. The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved. The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method.

• 出版日期2014
• 单位中国传媒大学