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The speech emotion recognition accuracy of prosody feature and voice quality feature declines with the decrease of SNR (Signal to Noise Ratio) of speech signals. In this paper, we propose novel sub-band spectral centroid weighted wavelet packet cepstral coefficients (W-WPCC) for robust speech emotion recognition. The W-WPCC feature is computed by combining(More)
OBJECTIVES Human immunodeficiency virus (HIV) and hepatitis B virus (HBV) share similar routes of transmission, and rapid progression of hepatic and immunodeficiency diseases has been observed in coinfected individuals. Our main objective was to investigate the molecular mechanism of HIV/HBV coinfections. METHODS We selected HIV infected and HIV/HBV(More)
A wavelet packet based adaptive filter-bank construction combined with Deep Belief Network(DBN) feature learning method is proposed for speech signal processing in this paper. On this basis, a set of acoustic features are extracted for speech emotion recognition, namely Coiflet Wavelet Packet Cepstral Coefficients (CWPCC). CWPCC extends the conventional(More)
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