基于模糊K近邻的模糊支持向量机的语音情感识别
Speech Emotion Recognition of FSVM Based on FKNN
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摘要: 基于模糊K近邻算法对模糊支持向量机中模糊类别隶属度的计算进行了改进，将距离与样本之间的关系相结合进行加权弥补了FSVM算法的不足.引入CCA算法对语音特征矢量进行降维处理，有效减小了特征之间的冗余信息，通过识别实验对传统的SVM、FSVM以及基于模糊K近邻的FSVM的算法性能进行了比较和分析.Abstract: In the process of calculating the fuzzy class membership function,the distance and relationships between the samples are weighted based on fuzzy K neighbor algorithm.In the experiment,firstly,the dimensions of the speech feature vector are reduced by CCA method.Then,with the results of experiment,the performance of traditional SVM,Fuzzy SVM,Fuzzy SVM based on Fuzzy K neighbor nearest algorithm is compared.
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