FUZZY LOGIC-BASED INTELLIGENT CONTROL FOR SVM SPEAKER VERIFICATION WITH THE SUPPORT OF GMM PRIOR INFORMATION
Ing-Jr Ding, Chih-Ta Yen, Zih-Jheng Lin · Transactions of the Canadian Society for Mechanical Engineering · 2013
In this paper, a fuzzy logic-based intelligent control (FLIC) scheme for support vector machine (SVM) speaker verification, called FLICSVM, is developed. The proposed FLICSVM method enhances SVM training by considering the property of training utterances for establishing the SVM model and therefore could further ensure the robustness of the SVM classifier on speaker verification. In FLICSVM, when establishing the SVM model in the training procedure, the popular fuzzy control methodology is employed to tune certain specific SVM parameter according to the prior information of SVM training utterances that is derived from Gaussian mixture model (GMM) calculations. Experimental results demonstrated that proposed FLICSVM is apparently superior to conventional SVM in the recognition accuracy.