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Method of setting optimum-partitioned classified neural network and method and apparatus for automatic labeling using optimum-partitioned classified neural network

机译:设置最佳划分的分类神经网络的方法以及使用最佳划分的分类神经网络进行自动标记的方法和设备

摘要

A method of automatic labeling using an optimum-partitioned classified neural network includes searching for neural networks having minimum errors with respect to a number of L phoneme combinations from a number of K neural network combinations generated at an initial stage or updated, updating weights during learning of the K neural networks by K phoneme combination groups searched with the same neural networks, and composing an optimum-partitioned classified neural network combination using the K neural networks of which a total error sum has converged; and tuning a phoneme boundary of a first label file by using the phoneme combination group classification result and the optimum-partitioned classified neural network combination, and generating a final label file reflecting the tuning result.
机译:一种使用最佳划分的分类神经网络进行自动标记的方法,包括从初始阶段生成或更新的K个神经网络组合中搜索相对于L个音素组合具有最小误差的神经网络,并在学习过程中更新权重通过在相同神经网络中搜索的K个音素组合组对K个神经网络进行分析,并使用总误差总和已收敛的K个神经网络组成最优划分的分类神经网络组合。通过使用音素组合组分类结果和最优划分的分类神经网络组合来调整第一标签文件的音素边界,并生成反映该调整结果的最终标签文件。

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