Speech Emotional Recognition Using Global and Time Sequence Structure Feature
全局和时序结构特征并用的语音信号情感特征识别方法

While the former method for emotional feature analysis in speech signal utili-zes global features, a novel method that is based on time sequence feature is proposed in this paper. For different number of vowels, three programming methods are proposed to normalize the length of the speech signal. Experiments are conducted on a task of 10 speakers, 1000 sentences including happy, anger, surprise and sorrowful emotions to demonstrate the effectiveness of the new method. The average recognition rate is as high as 94%.