Formant Based Linear Prediction Coefficients for Speaker Identification

被引：0

作者：

Srivastava, Sumit ^{[1
]}

Nandi, Pratibha

Sahoo, G. ^{[1
]}

Chandra, Mahesh

机构：

[1] BIT, Informat Technol Dept, Mesra 835215, Ranchi, India

来源：

2014 INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN) | 2014年

关键词：

LPC; Formant; Hindi digits; GMM;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Here Formant Based Linear Prediction Coefficient (FBLPC) features are proposed for speaker identification for all environments. Gaussian Mixture Models (GMMs) are used for classification of speakers. The identification performance of Linear Prediction Coefficient (LPC) features is computed and compared with the identification performance of FBLPC features. The performance of FBLPC features is found superior in clean and noisy environments. A database of fifty speakers for ten Hindi digits is used for simulation of results.

引用

页码：685 / 688

页数：4

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