Title: Threshold Selection Based on TZ Normalization for Speaker Verification
Abstract: For better decision-making in a speaker verification system, the threshold achieved by the minimum detection cost function (DCF) is determined. The bimodal distribution parameters of the output score based on the target speaker model are different, so it is difficult to estimate a mutual threshold. This paper proposes a novel score normalization-TZ normalization combined by the traditional zero normalization and the test normalization. Then, to obtain better robustness, a new method is introduced to improve the estimated threshold. Text-independent speaker verification experiments on the telephony NIST speaker recognition evaluation corpus show that the significant improvements for this new technique are effective compared to the traditional techniques.
Publication Year: 2005
Publication Date: 2005-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 1
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot