| 基于支持向量机的说话人识别研究 |
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| 引用本文： | 张振领,徐东平,贾仰理. 基于支持向量机的说话人识别研究[J]. 数字社区&智能家居, 2007, 2(7): 255 |
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| 作者姓名： | 张振领 徐东平 贾仰理 |
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| 作者单位： | 武汉理工大学计算机科学与技术学院，武汉理工大学计算机科学与技术学院，北京航空航天大学计算机学院 湖北武汉430063聊城大学计算机学院，山东聊城252059，湖北武汉430063，北京100083 |
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| 摘 要： | 解决说话人识别问题具有重要的理论价值和深远的实用意义,本文在研究支持向量机理论的基础上,采用支持向量机的分类算法实现说话人识别系统的训练和测试,并将小波去噪技术应用于说话人识别的预处理过程中,改善进入说话人识别系统的语音质量。实验表明,在说话人识别系统中,支持向量机结合小波去噪可以获得较好的识别率。
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| 关 键 词： | 说话人识别 支持向量机 小波去噪 机器学习 |
| 文章编号： | 1009-3044(2007)07-20255-01 |
| 修稿时间： | 2007-03-13 |
Speaker Recognition Research Based on Support Vector Machine |
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| ZHANG Zhen-ling,,XU Dong-ping,JIA Yang-li. Speaker Recognition Research Based on Support Vector Machine[J]. Digital Community & Smart Home, 2007, 2(7): 255 |
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| Authors: | ZHANG Zhen-ling XU Dong-ping JIA Yang-li |
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| Affiliation: | ZHANG Zhen-ling1,2,XU Dong-ping1,JIA Yang-li3 |
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| Abstract: | There are important theoretic value and far-reaching practical meaning to resolve the question of speaker recognition. SVM classification algorithm is used to realize the speaker recognition system's training and testing based on the research of Support Vector Machine theory. And wavelet de-noising technology is also applied to the pre-process to improve the quality of speech signal input into the speaker recognition system. Experimental results have shown that the speaker recognition system's recognition rate was greatly increased by the combination of SVM and wavelet de-nosing. |
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| Keywords: | Speaker Recognition Support Vector Machine(SVM) Wavelet De-noising Machine Learning |
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