Speaker Recognition Using Discriminant Neighborhood Embedding

被引：1

作者：

Liang Chunyan ^{[1
]}

Yuan Wenhao ^{[1
]}

Li Yanling ^{[2
]}

Xia Bin ^{[1
]}

Sun Wenzhu ^{[1
]}

机构：

[1] Shandong Univ Technol, Coll Comp Sci & Technol, Zibo 255049, Peoples R China

[2] Inner Mongolia Normal Univ, Coll Comp & Informat Engn, Hohhot 010022, Peoples R China

来源：

JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY | 2019年 / 41卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Speaker recognition; Total variability factor analysis; Neighborhood Preserving Embedding (NPE); Discriminant Neighborhood Embedding (DNE);

D O I：

10.11999/JEIT180761

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：

Discriminant Neighborhood Embedding (DNE) algorithm is introduced into the speaker recognition system. DNE is a manifold learning approach and aims at preserving the local neighborhood structure on the data manifold. As well, DNE has much more power in discrimination by sufficiently using the between-class discriminant information. The experimental results on the telephone-telephone core condition of the NIST 2010 Speaker Recognition Evaluation (SRE) dataset indicate the effectiveness of DNE algorithm.

引用

页码：1774 / 1778

页数：5

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