首页> 外国专利> METHOD FOR COMPOSING CLASSIFICATION NEURAL NETWORK OF OPTIMUM SECTION AND AUTOMATIC LABELLING METHOD AND DEVICE USING CLASSIFICATION NEURAL NETWORK OF OPTIMUM SECTION

METHOD FOR COMPOSING CLASSIFICATION NEURAL NETWORK OF OPTIMUM SECTION AND AUTOMATIC LABELLING METHOD AND DEVICE USING CLASSIFICATION NEURAL NETWORK OF OPTIMUM SECTION

机译:最优部分的分类神经网络的组合方法和自动标记方法及采用最优部分的分类神经网络的设备

摘要

PPROBLEM TO BE SOLVED: To provide a method for composing a classification neural network of an optimum section and an automatic labelling method and device using classification neural network of the optimum section. PSOLUTION: The automatic labelling method using classification neural network of the optimum section comprises a step (a) that searches a neural network having a minimum error for each of L combinations of phoneme from K neural network sets created or updated in an initial stage, learns the K sets of the neural networks by the group of K combinations of phoneme searched from the same neural network and updates the weighted value, and composes K neural networks obtained at the time when the sum of the total error of K neural networks is converged with individual errors converged with the classification neural network sets of the optimum section; and a step (b) that corrects a boundary of phoneme of the primary label file using the phoneme combination group classification result and the classification neural network sets of the optimum section provided in the step (a), and creates a final label file reflecting the correction result. PCOPYRIGHT: (C)2004,JPO&NCIPI
机译:

要解决的问题:提供一种构成最佳部分的分类神经网络的方法以及一种使用最佳部分的分类神经网络的自动标记方法和装置。解决方案:使用最佳部分的分类神经网络进行自动标记的方法包括步骤(a),该步骤从初始创建或更新的K个神经网络集中为L个音素组合中的每个误差搜索误差最小的神经网络。阶段,通过从相同神经网络搜索的K个音素组合组学习K个神经网络,并更新加权值,并组成在K个神经网络的总误差之和时获得的K个神经网络。收敛于个体误差,收敛于最优区间的分类神经网络集;步骤(b),其使用步骤(a)中提供的音素组合组分类结果和最佳区间的分类神经网络集来校正主标签文件的音素边界,并创建反映标签内容的最终标签文件。校正结果。

版权:(C)2004,日本特许厅和日本国家唱片公司

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