Kernel-based speaker clustering for rapid speaker adaptation

被引：0

作者：

Hazrati, Dooz ^{[1
]}

Ahadi, S. M. ^{[1
]}

Sadjadi, Omid ^{[1
]}

机构：

[1] Tehran Polytech, EE Dept, Speech Proc Res Lab, Tehran, Iran

来源：

PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: NEW GENERATIONS | 2008年

关键词：

speaker adaptation; Kernel method; one-class SVM; speaker clustering;

D O I：

10.1109/ITNG.2008.176

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Speaker clustering is a widely used technique in speaker adaptation, especially since it can be easily combined with adaptation methods such as MAP or MLLR. In this paper we present and evaluate a new speaker adaptation method using a kernel-based speaker clustering algorithm inspired by the classical K-means and based on one-class support vector machines. We find that this adaptation method outperforms other conventional clustering techniques such as K-means and gender clustering with only small amounts of adaptation data (i.e. less than 10sec.).

引用

页码：1287 / 1289

页数：3

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