A modified group vector quantization algorithm for speaker identification

被引：0
|
作者：
Abu El-Yazeed, MF [1 ]
Kader, NSA [1 ]
El-Henawy, MM [1 ]
机构：
[1] Cairo Univ, Fac Engn, Dept Elect & Comm, Giza 12211, Egypt
来源：
PROCEEDINGS OF THE 46TH IEEE INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS & SYSTEMS, VOLS 1-3 | 2003年
关键词：
group vector quantization; speaker identification; text independent;
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：
In this paper, a modification to the group vector quantization (GVQ) discriminative training algorithm is proposed to train VQ codebooks for closed set speaker identification. The proposed algorithm, referred to as modified GVQ (MGVQ), shifts the decision surfaces between speakers smoothly toward the Bayes limits. This is achieved by varying the learning rate during training iterations. The proposed MGVQ algorithm achieves higher speaker identification rate compared to the standard GVQ.
引用
收藏
页码：629 / 632
页数：4
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