首页> 外国专利> DISPERSION CORRECTION PARAMETER ESTIMATION DEVICE, VOICE RECOGNITION SYSTEM, DISPERSION CORRECTION PARAMETER ESTIMATION METHOD, VOICE RECOGNITION METHOD AND PROGRAM

DISPERSION CORRECTION PARAMETER ESTIMATION DEVICE, VOICE RECOGNITION SYSTEM, DISPERSION CORRECTION PARAMETER ESTIMATION METHOD, VOICE RECOGNITION METHOD AND PROGRAM

机译:色散校正参数估计装置,语音识别系统,色散校正参数估计方法,语音识别方法和程序

摘要

PROBLEM TO BE SOLVED: To provide a dispersion correction parameter estimation device that stably and accurately estimates a dispersion correction parameter through discriminative learning.;SOLUTION: A dispersion correction parameter estimation device executes the steps of: generating a dispersion correction parameter; using the dispersion correction parameter to correct a dispersion parameter of a Gauss distribution included in a mixed Gauss distribution model; obtaining a degree of difference from a correct answer symbol series with a predetermined particle size, with respect to each opposing candidate symbol series to be obtained through voice recognition of a feature quantity of voice data for learning, on the basis of an acoustic model including the corrected dispersion parameter; obtaining a differential value when using the Gauss distribution dispersion correction parameter to differentiate an objective function of a discriminative learning criterion, on the basis of a language probability of the opposing candidate symbol series, an acoustic score to be obtained by an acoustic model on the basis of the feature quantity of voice data for learning and the opposing candidate symbol series and the degree of difference; and updating the Gauss distribution dispersion correction parameter by changing the Gauss distribution correction parameter according to the differential value.;COPYRIGHT: (C)2013,JPO&INPIT
机译:解决的问题:提供一种色散校正参数估计装置,该装置通过判别学习稳定而准确地估计色散校正参数。解决方案:色散校正参数估计装置执行以下步骤:产生色散校正参数;使用色散校正参数来校正包括在混合高斯分布模型中的高斯分布的色散参数;根据包括以下内容的声学模型,对于通过学习要用的语音数据的特征量进行语音识别而获得的每个相对的候选符号系列,从具有预定粒度的正确答案符号系列中获得差异度,校正后的色散参数;当使用高斯分布色散校正参数来区分判别学习准则的目标函数时,获得差分值,基于相对候选符号系列的语言概率,基于声学模型获得声学分数用于学习的语音数据的特征量和相对的候选符号系列的差异程度;通过根据微分值改变高斯分布校正参数来更新和更新高斯分布色散校正参数。;版权所有:(C)2013,JPO&INPIT

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