Adaptive Wavelet Packet Filter-Bank Based Acoustic Feature for Speech Emotion Recognition

摘要

In this paper, a wavelet packet based adaptive filter-bank construction method is proposed, with additive Fisher ratio used as wavelet packet tree pruning criterion. A novel acoustic feature named discriminative band wavelet packet power coefficients (db-WPPC) is proposed and on this basis, a speech emotion recognition system is constructed. Experimental results show that the proposed feature improves emotion recognition performance over the conventional MFCC feature.