Abstract: To solve the problem that the dimension of the speech emotion characteristic value is big and it is difficult to train, a new speech emotion recognition model, MFCCG-PCA, is put forward by the combination of the MFCC model and the PCA model. Multiple sets of experiments show that the MFCCG-PCA model has larger performance improvement than general MFCC model in the aspect of speech emotion recognition.

Key words: speech emotion recognition, MFCC, PCA, MFCCG-PCA, SVM, CASIA

摘要： 针对语音情感值维度大、难处理的问题, 结合MFCC改进算法和PCA模型, 进行二次优化, 提出一种新的语音情感值提取模型MFCCG-PCA。多组实验表明, 相比一般的MFCC模型, MFCCG-PCA模型在语音情感识别方面的性能有较大提高。

关键词: 语音情感, 梅尔频率倒谱系数, 主成分析, MFCCG-PCA, 支持向量机, CASIA汉语情感语料库