融合语音情感词局部特征的语音情感识别方法

为有效利用语音情感词局部特征,提出了一种融合情感词局部特征与语音语句全局特征的语音情感识别方法。该方法依赖于语音情感词典的声学特征库,提取出语音语句中是否包含情感词及情感词密度等局部特征,并与全局声学特征进行融合,再通过机器学习算法建模和识别语音情感。对比实验结果表明,融合语音情感词局部特征与全局特征的语音情感识别方法能取得更好的效果,局部特征的引入能有效提高语音情感识别准确率。

Speech emotion recognition integrating local features of sentiment words

To improve efficient utilization of local features in sentiment words of speech, we propose a new speech emotion recognition method by fusing local features of sentiment words and global features. Based on the acoustic features of the emotional dictionary, we extract local features, such as sentiment word existence in the statement and its density. Then by fusing the global features of speech, we can recognize the speech emotion through modeling with machine learning algorithms. The comparative experiment results show that the proposed method can gain very good performance, and the introduction of local features can improve the precision of speech emotion recognition.