Design of a Text Independent Speaker Recognition System

被引：0
|
作者：
Ozaydin, Selma [1 ]
机构：
[1] Cankaya Univ, Elect & Commun Engn, Ankara, Turkey
来源：
2017 INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTING TECHNOLOGIES AND APPLICATIONS (ICECTA) | 2017年
关键词：
speaker recognition; voice recognition; gaussian mixture model; biometrics; HTK;
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：
This paper presents the design of a text independent speaker recognition system based on Mel-Frequency Cepstrum Coefficients and Gaussian Mixture Models. HTK speech recognition toolkit is used in the design of speaker models. The system is aimed to use it as a biometric authentication system. The experiments were performed on speech data consist of 134 speakers from YOHO database for different training conditions. The increase of the proposed system performance is observed with the decrease of Equal Error Rate. Experiment results show that the system gives the best recognition performance for Gaussian mixture model with 64 mixtures.
引用
收藏
页码：55 / 59
页数：5
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