Speaker identification based on GMM with embedded AANN

被引：0
|
作者：
Chen C.-B. [1 ]
Zhao L. [1 ]
机构：
[1] School of Information Science and Engineering, Southeast University
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2010年 / 32卷 / 03期
关键词：
Auto-Associate Neural Network (AANN); Embedded; Gaussian Mixed Model (GMM); Speaker identification;
D O I：
10.3724/SP.J.1146.2008.00275
中图分类号：
学科分类号：
摘要：
In this paper, a modified Gaussian Mixed Model (GMM) with an embedded Auto-Associate Neural Network (AANN) is proposed. It integrates the merits of GMM and AANN. GMM and AANN as a whole are trained by means of Maximum Likelihood (ML). In the process of training, the parameters of GMM and AANN are updated alternately. AANN reshapes the distribution of the data and improves the similarity of the data in one class. Experiments show that the proposed system improves accuracy rate against baseline GMM at all SNR, maximum to 19%.
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页码：528 / 532
页数：4
相关论文
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