Parameter settings for speaker identification using Gaussian mixture model

被引：0
|
作者：
Eskidere, Oe [1 ]
Ertas, F. [2 ]
机构：
[1] Uludag Univ Tekn Bilimler MYO, Bursa, Turkey
[2] Uludag Univ Muh Mim Fak, Bursa, Turkey
来源：
2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3 | 2007年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the impact of the number of Gaussian mixtures, the duration of training and testing sessions, and the number of speakers on speaker identification has been investigated using clean speech (TIMIT) and telephone speech (NTIMIT) databases. Employing the parameters that provide the maximum performance, 100% and 85.71% identification rates have been obtained for the TIMIT and NTIMIT databases, respectively.
引用
收藏
页码：495 / +
页数：2
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