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Pre-processing voice signals for voice recognition systems

机译:预处理语音识别系统的语音信号

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摘要

The article considers the pre-processing voice signals for voice recognition systems based on the use of artificial neural networks. Based segmentation preprocessing is put in the speech signal according to a phonetic transcription of language, in order to reduce the amount of data supplied to the input of the neural network, which considerably improves its input data sensitivity. Application of numerical methods in processing will reduce acoustic noise impact on the speech signal segmentation, which will more accurately identify the areas of classification. Simulation results of the speech signal partition into components are shown, i.e. the selection of phonemes which will be the voice message classification.
机译:本文考虑了基于人工神经网络的语音识别系统的预处理语音信号。为了减少提供给神经网络输入的数据量,根据语言的语音转录对语音信号进行了基于分段的预处理,从而大大提高了其输入数据的敏感性。数值方法在处理中的应用将减少声音噪声对语音信号分割的影响,这将更准确地识别分类区域。示出了将语音信号划分为多个分量的仿真结果,即,选择将成为语音消息分类的音素。

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