Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (35): 123-125.
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PAN Ping, HE Zhaoxia
Online:
Published:
潘 平,何朝霞
Abstract: Speaker feature parameter extraction directly affects the establishment of recognition model. Parameter extraction methods of MFCC and LPC, respectively regard local low-frequency information and global AR signal as the main feature. In this paper, a method of speaker spectrum feature extraction based on duffing stochastic resonance is proposed. Simulation results show that this method, which provides a more elaborate recognition model for speaker recognition, can identify tiny differences of spectrum among speakers and extract basic characteristics of spectrum effectively.
Key words: duffing stochastic resonance, Speaker Recognition(SR), feature parameter extraction
摘要: 说话人特征参数的提取直接影响识别模型的建立,MFCC与LPC参数提取方法,分别以局域低频信息和全局AR信号为主要特征。提出一种基于duffing随机共振的说话人频谱特征提取方法。仿真结果表明,该方法能识别说话人之间频谱的微小差别,有效地提取说话人频谱的基本特征,从而为说话人识别模型提供更为精细的识别模型。
关键词: duffing随机共振, 说话人识别(SR), 特征提取
PAN Ping, HE Zhaoxia. Method of speaker feature parameter extraction based on duffing stochastic resonance[J]. Computer Engineering and Applications, 2012, 48(35): 123-125.
潘 平,何朝霞. 基于duffing随机共振的说话人特征提取方法[J]. 计算机工程与应用, 2012, 48(35): 123-125.
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