Hierarchical fuzzy speaker identification based on FCM and FSVM
- Resource Type
- Conference
- Authors
- Xing, YuJuan; Li, Hengjie; Tan, Ping
- Source
- 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on. :311-315 May, 2012
- Subject
- Components, Circuits, Devices and Systems
Computing and Processing
Communication, Networking and Broadcast Technologies
Kernel
Accuracy
Training
Optimization
Training data
Support vector machine classification
support vector machine
FCM Clustering
speaker identification
- Language
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.