Speaker Recognition Based on a Novel Hybrid Algorithm

摘要：

　　Using Probabilistic Neural Network (PNN) to recognize speaker is one of the research of branch of speaker recognition.PNNs ability of recognition is so dependent on the value of its smoothing factor that its ability of recognition is not that good.To solve this problem,we proposed a novel hybrid algorithm (DFOA-SOM-PNN) to improve PNNs ability of recognition.Firstly,it uses SOM to cluster MFCC speech characteristics parameters which can reduce storage of data and calculation,and well reflect feature of MFCC.Secondly,it uses an improved algorithm of Fruit fly Optimization Algorithm (FOA): Double group FOA (DFOA),which optimizes the smooth factor of PNN.The experimental results show that DFOA have better global convergence and fast convergence speed than FOA,and the proposed hybrid algorithm has better performance in speaker recognition.

关键词： speaker recognition Fruit Fly Optimization Algorithm Double group FOA SOM PNN

作者: Hui Zhou Fan-Zi Zeng

作者单位: Information Science and Engineering Hunan University Changsha, China

会议类型: 国际会议

会议名称: 2012 IEEE 14th International Conference on Communication Technology(2012年第十四届通信技术国际会议(ICCT 2012))

会议地点: 成都

会议语种:英文

页码: 1359-1363

在线出版日期: 2012-11-09（万方平台首次上网日期，不代表论文的发表时间）