Speech emotion recognition using kernel sparse representation based classifier
Pulkit Sharma, Vinayak Abrol, Abhijeet Sachdev, A. D. Dileep · 2016
In this paper, we propose to use a kernel sparse representation based classifier (KSRC) for the task of speech emotion recognition. Further, the recognition performance using the KSRC is improved by imposing a group sparsity constraint. The speech utterances with same emotion may have different duration, but the frame sequence information does not play a crucial role in this task. Hence, in this work, we propose to use dynamic kernels which explicitly models the variability in duration of speech signals. Experimental results demonstrate that, given a suitable kernel, KSRC with group sparsity constraint performs better as compared to the state-of-the-art support vector machines (SVM) based classifiers.