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中文摘要：
在NIST SRE 2012年评测和实际应用中,可以用说话人的多个语音样本来注册说话人模型,并且这些语音样本取自于各种各样的信道。本文基于PLDA,尝试了多种打分方法,并提出一种新的得分规整技术,在NIST SRE 2012核心测试集上,EER平均提升26.0%,MinCost平均提升12.4%。
英文摘要：
In NIST SRE 2012 evaluation and practical applications,multiple recordings,which come from various channel conditions, can be used to train a speaker model. Based on PLDA,this paper will try several score methods and propose one score normalization technique. Equal error rate and minimum cost has been relatively improved 26. 0% and 12. 4% respectively on NIST SRE 2012 core test corpus.
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