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A Log-Index Weighted Cepstral Distance Measure for Speech Recognition
作者姓名:Zheng Fang  Wu Wenhu  Fang Ditang
作者单位:[1]DepartmentofComputerScienceandTechnology,TsinghuaUniversity,Beijing100084 [2]DepartmentofComputerScience,TsinghuaUniversity,Beijing100084
摘    要:A log-index weighted cepstral distance measure is proposed and tested in speacker-independent and speaker-dependent isolated word recognition systems using statistic techniques.The weights for the cepstral coefficients of this measure equal the logarithm of the corresponding indices.The experimental results show that this kind of measure works better than any other weighted Euclidean cepstral distance measures on three speech databases.The error rate obtained using this measure is about 1.8 percent for three databases on average,which is a 25% reduction from that obtained using other measures,and a 40% reduction from that obtained using Log Likelihood Ratio(LLR)measure.The experimental results also show that this kind of distance measure woks well in both speaker-dependent and speaker-independent speech recognition systems.

关 键 词:语言识别  距离测量  对数指数  计算机

A log-index weighted cepstral distance measure for speech recognition
Zheng Fang,Wu Wenhu,Fang Ditang.A Log-Index Weighted Cepstral Distance Measure for Speech Recognition[J].Journal of Computer Science and Technology,1997,12(2):177-184.
Authors:Fang Zheng  Wenhu Wu  Ditang Fang
Affiliation:Department of Computer Science and Technology; Tsinghua University; Beijing 100084; E-mail: fzheng@sp.cs.tsinghua.edu.cn;
Abstract:A log-index weighted cepstral distance measure is proposed and tested in speaker-independent and speaker-dependent isolated word recognition systems using statistic techniques. The weights for the cepstral coefficients of this measure equal the logarithm of the corresponding indices. The experimental results show that this kind of measure works better than any other weighted Euclidean cepstral distance measures on three speech databases. The error rate obtained using this measure is about 1.8 percent for three databases on average, which is a 25% reduction from that obtained using other measures, and a 40% reduction from that obtained using Log Likelihood Ratio (LLR) measure. The experimental results also show that this kind of distance measure works well in both speaker-dependent and speaker-independent speech recognition systems.
Keywords:Log-index weighted cepstral distance measure  speech recognition
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