基于MFCC和KMCG聚类算法的矢量量化说话人识别

H. B. Kekre, V. Bharadi, A. Sawant, O. Kadam, P. Lanke, R. Lodhiya
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引用次数: 17

摘要

说话人识别系统是利用语音信号进行生物识别的应用之一。在本文中,我们使用Mel频率Capestral系数(MFCC)和Kekre的中位数码本生成算法(KMCG)的组合实现了一个说话人识别系统。MFCC算法用于特征提取,KMCG算法在码本生成和特征匹配中起着重要作用。为了实现简单,系统被构建为文本依赖系统,即所有用户使用的通用文本。KMCG算法实现简单,精度高。
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Speaker recognition using Vector Quantization by MFCC and KMCG clustering algorithm
Speaker identification system is one of the applications of biometric using voice signal. In this paper we have implemented a speaker recognition system using a combination of Mel Frequency Capestral Coefficients (MFCC) & Kekre's Median Codebook Generation Algorithm (KMCG). The MFCC algorithm is used for feature extraction while the KMCG algorithm plays important role in code book generation and feature matching. For implementation simplicity the system is built as a text dependent system, i.e. common text used by all users. KMCG algorithm provides implementation simplicity along with high level of accuracy.
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