Robust Speech Emotion Recognition with Novel Sub-Band Spectral Centroid Weighted Wavelet Packet Feature

In this paper, we propose novel sub-band spectral centroid weighted wavelet packet cepstral coefficients (W-WPCC) for noise-robust speech emotion recognition. Experimental results show that the W-WPCC feature demonstrates better noise-robustness in noisy environments.

[1]  Zhihong Zeng,et al.  Audio–Visual Affective Expression Recognition Through Multistream Fused HMM , 2008, IEEE Transactions on Multimedia.

[2]  Ronald R. Coifman,et al.  Wavelet analysis and signal processing , 1990 .

[3]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[4]  Michael S. Scordilis,et al.  Spoken Emotion Recognition Using Glottal Symmetry , 2011, EURASIP J. Adv. Signal Process..

[5]  Abhijit Karmakar,et al.  Design of Optimal Wavelet Packet Trees Based on Auditory Perception Criterion , 2007, IEEE Signal Processing Letters.

[6]  Emanuel Parzen,et al.  Autoregressive Spectral Estimation. , 1983 .

[7]  ChunChen,et al.  EMOTION RECOGNITION FROM NOISY SPEECH , 2006 .

[8]  Hugo Fastl,et al.  Psychoacoustics: Facts and Models , 1990 .

[9]  Astrid Paeschke,et al.  A database of German emotional speech , 2005, INTERSPEECH.

[10]  Kuldip K. Paliwal,et al.  Spectral subband centroid features for speech recognition , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).