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

被引：1

作者：

Zha, Cheng ^{[1
,2
]}

Zhang, Xinrang ^{[1
]}

Zhao, Li ^{[1
]}

Liang, Ruiyu ^{[3
]}

机构：

[1] Southeast Univ, Sch Informat Sci & Engn, Nanjing 210096, Jiangsu, Peoples R China

[2] Guizhou Univ, Coll Comp Sci & Informat, Guiyang 550025, Peoples R China

[3] Nanjing Inst Technol, Sch Commun Engn, Nanjing 211167, Jiangsu, Peoples R China

来源：

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES | 2016年 / E99A卷 / 03期

关键词：

multiple kernel learning; multi-level features; automatic segmentation; collaborative representation;

D O I：

10.1587/transfun.E99.A.756

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：756 / 759

页数：4

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