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

Cheng ZHA; Xinrang ZHANG; Li ZHAO; Ruiyu LIANG

doi:10.1587/transfun.E99.A.756

Regular Section

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

Cheng ZHA, Xinrang ZHANG, Li ZHAO, Ruiyu LIANG

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Keywords: multiple kernel learning, multi-level features, automatic segmentation, collaborative representation

JOURNAL RESTRICTED ACCESS

2016 Volume E99.A Issue 3 Pages 756-759

DOI https://doi.org/10.1587/transfun.E99.A.756

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Abstract

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.

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