Speaker-Independent Speech Emotion Recognition Based Multiple Kernel Learning of Collaborative Representation

Cheng ZHA  Xinrang ZHANG  Li ZHAO  Ruiyu LIANG  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E99-A   No.3   pp.756-759
Publication Date: 2016/03/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E99.A.756
Type of Manuscript: LETTER
Category: Engineering Acoustics
multiple kernel learning,  multi-level features,  automatic segmentation,  collaborative representation,  

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We propose a novel multiple kernel learning (MKL) method using a collaborative representation constraint, called CR-MKL, for fusing the emotion information from multi-level features. To this end, the similarity and distinctiveness of multi-level features are learned in the kernels-induced space using the weighting distance measure. Our method achieves better performance than existing methods by using the voiced-level and unvoiced-level features.