Speaker Verification Using Gaussian Mixture Model

被引：0

作者：

Jagtap, Shilpa S. ^{[1
]}

Bhalke, D. G.

机构：

[1] Rajarshi Shahu Coll Engn, Dept Elect & Telecommun Engn, Tathawade, India

来源：

2015 INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING (ICPC) | 2015年

关键词：

EER; feature extraction; GMM; MFCC; pitch;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, speaker verification system using Gaussian Mixture Model (GMM) is proposed. The proposed system consists of pre- processing, feature extraction, modelling and classification stage. The pre- processing is used to remove silent part of signal to reduce computational complexity. Pitch frequency and Mel Frequency Cepstral Coefficients(MFCC) are used as a feature vector for speaker verification system. Modelling is done using different combination of Gaussian mixture models. Simple distance measures are used for the classification between reference and the test signal.

引用

页数：5

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