RESTRICTED BOLTZMANN MACHINE SUPERVECTORS FOR SPEAKER RECOGNITION

被引：0
|
作者：
Ghahabi, Omid [1 ]
Hernando, Javier [1 ]
机构：
[1] Univ Politecn Cataluna, BarcelonaTech, TALP Res Ctr, Dept Signal Theory & Commun, Barcelona, Spain
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | 2015年
关键词：
Speaker Recognition; Supervector; Restricted Boltzmann Machine;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The use of Restricted Boltzmann Machines (RBM) is proposed in this paper as a non-linear transformation of GMM supervectors for speaker recognition. It will be shown that the RBM transformation will increase the discrimination power of raw GMM supervectors for speaker recognition. The experimental results on the core test condition of the NIST SRE 2006 corpus show that the proposed RBM supervectors will achieve a comparable performance to i-vectors. Furthermore, the combination of RBM supevectors and i-vectors in the score level improves the performance of the i-vector approach by more than 10% in terms of EER.
引用
收藏
页码：4804 / 4808
页数：5
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