A robust speaker-adaptive and text-prompted speaker verification system

被引：2

作者：

Hong, Qingyang ^{[1
]}

Wang, Sheng ^{[1
]}

Liu, Zhijian ^{[1
]}

机构：

[1] Department of Cognitive Science and Fujian Key Lab of Brain-Like Intelligent System Xiamen University, Xiamen

来源：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 2014年 / 8833卷

关键词：

Recording playback; Speaker Verification;

D O I：

10.1007/978-3-319-12484-1_43

中图分类号：

学科分类号：

摘要：

Currently, the recording playback attack has become a major security risk for speaker verification. The text-independent or text-dependent system is being troubled by it. In this paper, we propose an effective text-prompted system to overcome this problem, in which speaker verification and speech recognition are combined together. We further adopt speaker-adaptive hidden Markov model (HMM) so as to improve the verification performance. After HMM-based speaker adaptation, this system needs not to be retrained at each verification step. Experimental results demonstrated that the proposed method had quite good performance with the equal error rate (EER) lower than 2% and was also robust for different cases. © Springer International Publishing Switzerland 2014.

引用

页码：385 / 393

页数：8

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