標題: Cluster-based support vector machines in text-independent speaker identification
作者: Sun, SY
Tseng, CL
Chen, YH
Chuang, SC
Fu, HC
資訊工程學系
Department of Computer Science
公開日期: 2004
摘要: Based on Statistical learning theory, Support Vector Machines(SVM) is a powerful tool for various classification problems, such as pattern recognition and speaker identification etc. However, Training SVM consumes large memory and long computing time. This paper proposes a cluster-based learning methodology to reduce training time and the memory size for SVM. By using k-means based clustering technique, training data at boundary of each cluster were selected for SVM learning. We also applied this technique to text-independent speaker identification problems. Without deteriorating recognition performance, the training data and time can be reduced up to 75% and 87.5% respectively.
URI: http://hdl.handle.net/11536/18207
ISBN: 0-7803-8359-1
ISSN: 1098-7576
期刊: 2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS
起始頁: 729
結束頁: 734
顯示於類別:會議論文