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《Journal of Tsinghua University(Science and Technology)》 2017-10
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Weighted phone log-likelihood ratio feature for spoken language recognition

ZHANG Jian;XU Jie;BAO Xiuguo;ZHOU Ruohua;YAN Yonghong;Institute of Acoustics,Chinese Academy of Sciences;National Computer Network Emergency Response Technical Team Coordination Center of China;  
The extraction of linguistic discriminative features is one of the fundamental issues in spoken language recognition(SLR).The frame level phone log-likelihood ratio(PLLR)has been recently introduced to improve language recognition.In this paper,the F-ratio analysis method is used to analyze the contributions of different SLR feature vector dimensions.Then,a weighted phone log-likelihood ratio(WPLLR)feature is used to more heavily weight those dimensions with high F-ratio values.Tests on the National Institute of Standards and Technology(NIST)2007 dataset for SLR show the effectiveness of this feature, with significant relative improvements in the average cost performance and equal error rate compared with the PLLR feature.
【Fund】: 国家自然科学基金资助项目(11461141004 91120001 61271426);; 国家“八六三”高技术项目(2012AA012503);; 中国科学院战略性先导科技专项(XDA06030100 XDA06030500);; 中科院重点部署项目(KGZD-EW-103-2)
【CateGory Index】: TN912.34
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