Hierarchical fuzzy speaker identification based on FCM and FSVM

Abstract

Unclassifiable audio data exists when the conventional SVM was utilized to make classification in the speaker identification. To overcome this problem, this paper proposes a novel hierarchical fuzzy speaker identification method based on fuzzy c-means (FCM) clustering and fuzzy support vector machine (FSVM). Two phases are employed to construct the proposed system. Firstly, the FCM clustering technique is utilized to partition the whole training dataset into several clusters which has its own cluster center. And then, FSVM is trained by the cluster centers to make final decision and process the unclassifiable data. Experiment results show that the proposed method heightens identification accuracy of system remarkablely compared with the baseline SVM speaker identification system.