Abstract: Recently, studies have been performed for speech emotion recognition. However, little research focused on the emotion of the elderly, especially the lonely elderly. In this paper, we propose a six layer Wavelet Packet Coefficients Model for speech emotion recognition of the Chinese elderly. Six layer Wavelet Packet Coefficients, Mel Frequency Cepstrum Coefficient and the Fourier Parameter features are extracted from speech emotion database of Chinese elderly, respectively. Experimental results show that the six layer wavelet packet coefficients features are effective for recognizing emotions from speech. In particularly, when combining these three features, the recognition rates of the elderly can be improved.
Keywords: Six Layer Wavelet Packet Coefficients, Mel Frequency Cepstrum Coefficient, Fourier Parameter, elderly