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一种基于改进得分分布的查询项特定阈值方法*

DOI: 10.16451/j.cnki.issn1003-6059.201505007, PP. 437-442

Keywords: 得分分布,查询项特定阈值,K-means聚类,语音查询项检索

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Abstract:

为提高语音查询项检索系统的准确率,提出一种基于改进得分分布的查询项特定阈值方法.在系统判决阶段,根据每个查询项的后验得分分布设定不同阈值.后验得分分布用指数混合模型描述,通过无监督的最大期望(EM)算法估计模型参数,最后根据贝叶斯最小风险准则计算阈值.针对EM算法对初始值较为敏感的问题,初始化时采用K-means聚类算法代替随机初始化方法,首先将候选结果得分分为两类,然后计算每类的先验分布并用最大似然法估计模型参数的初始值.实验结果表明该阈值方法有更好的检索性能.

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