Speech Emotion Recognition Based on Coiflet Wavelet Packet Cepstral Coefficients
A wavelet packet based adaptive filter-bank construction method is proposed for speech signal processing in this paper.On this basis,a set of acoustic features are proposed for speech emotion recognition,namely Coiflet Wavelet Packet Cepstral Coefficients (CWPCC).CWPCC extends the conventional Mel-Frequency Cepstral Coefficients (MFCC) by adapting the filter-bank structure according to the decision task; Speech emotion recognition system is constructed with the proposed feature set and Gaussian mixture model as classifier.Experimental results on Berlin emotional speech database show that the Coiflet Wavelet Packet is more suitable in speech emotion recognition than other Wavelet Packets and proposed features improve emotion recognition performance over the conventional features.
Speech emotion recognition Coiflet Wavelet packets Cepstral Coefficients (CWPCC) Acoustic features
Yongming Huang Ao Wu Guobao Zhang Yue Li
School of Automation,Southeast University,Nanjing 210096,China;Key Laboratory of Measurement and Control of Complex Systems of Engineering,Ministry of Education
国际会议
Chinese Conference on Pattern Recognition, CCPR(2014年全国模式识别学术会议)
长沙
英文
436-443
2014-11-01（万方平台首次上网日期，不代表论文的发表时间）