Journal of South China University of Technology (Natural Science Edition) ›› 2015, Vol. 43 ›› Issue (5): 100-106.doi: 10.3969/j.issn.1000-565X.2015.05.016

• Computer Science & Technology • Previous Articles     Next Articles

Logistic Kernel Function and its Application to Speech Recognition

Liu Xiao-feng1 Zhang Xue-ying2 Zizhong John Wang3   

  1. 1． College of Mathematics，Taiyuan University of Technology，Taiyuan 030024，Shanxi，China;2． College of Information Engineering，Taiyuan University of Technology，Taiyuan 030024，Shanxi，China;3． Department of Mathematics and Computer Science，Virginia Wesleyan College，Norfolk 23502，Virginia，USA
  • Received:2014-10-08 Revised:2014-12-19 Online:2015-05-25 Published:2015-05-07
  • Contact: 张雪英(1964-)，女，教授，博士生导师，主要从事语音信号处理研究． E-mail:tyzhangxy@163.com
  • About author:刘晓峰(1979-)，男，讲师，博士生，主要从事智能计算研究． E-mail: liuxinyu1206@163． com
  • Supported by:
    Supported by the National Natural Science Foundation of China(61072087)

PDF

361

Abstract: Kernel function is the core of support vector machine (SVM) and directly affects the performance of SVM． In order to improve the learning ability and generalization ability of SVM for speech recognition，a Logistic kernel function，which is proved to be a Mercer kernel function，is presented． Experimental results on bi-spiral and speech recognition problems show that the presented Logistic kernel function is effective and performs better than linear，polynomial，radial basis and exponential radial basis kernel functions，especially in the case of speech rec-ognition．

Key words: Logistic kernel function, speech recognition, support vector machines, Mercer kernel