2S-Norm: A New Score Normalization for a GMM Based Text-Independent Speaker Identification System

被引：0
作者：
Van Huy Nguyen [1 ]
机构：
[1] Thai Nguyen Univ Technol, Thai Nguyen, Vietnam
来源：
ADVANCES IN ENGINEERING RESEARCH AND APPLICATION | 2019年 / 63卷
关键词：
Speaker identification; Score normalization; Decision threshold 2S-Norm; T-Norm; Z-Norm;
D O I：
10.1007/978-3-030-04792-4_5
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper presents a new score normalization method for speaker identification using Gaussian Mixture Model (GMM). The new normalization method has two main advantages: (1) the thresholds are independent to dataset and mapped to the range of [0% divided by 100%] corresponding to your expected accuracy of the system and (2) better performance comparing to common methods. The experimental results suggest the viability of the proposed approach in terms of shortening the development time and providing regular update for model's parameters.
引用
收藏
页码：9 / 15
页数：7
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