Abstract
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.
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Li, Y., Zhang, G., Huang, Y. (2013). Adaptive Wavelet Packet Filter-Bank Based Acoustic Feature for Speech Emotion Recognition. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_40
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DOI: https://doi.org/10.1007/978-3-642-38466-0_40
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