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An Intelligent System for English Pronunciation Correction

机译:智能英语发音纠正系统

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English pronunciation correction highly relies on the English teaching quality, therefore, in this paper, we propose a novel intelligent system for English pronunciation correction based on both Convolutional neural networks (CNN) and voiceprint proof. CNN refers to a multi-layer neural network, in which each layer contains multiple 2D planes and each plane is made up of a lot of independent neurons. We read the voice signal of speakers in advance, and then handle the original voices based on the CNN model. Then, the MFCC features are extracted and input to the CNN and voiceprint recognition is achieved by analyzing the output of CNN. Afterwards, English pronunciations are corrected through comparing the voiceprint of the target user to the standard pronunciation. Finally, experimental results demonstrate that the proposed method is able to achieve high voiceprint recognition rate for various experiment settings.
机译:英语语音校正高度依赖于英语教学质量,因此,本文提出了一种基于卷积神经网络(CNN)和声纹证明的新型智能英语语音校正系统。 CNN是指多层神经网络,其中每一层包含多个2D平面,并且每个平面由许多独立的神经元组成。我们预先读取扬声器的语音信号,然后基于CNN模型处理原始语音。然后,提取MFCC特征并将其输入到CNN,并通过分析CNN的输出来实现声纹识别。然后,通过将目标用户的声纹与标准发音进行比较,对英语发音进行校正。最后,实验结果表明,该方法能够在各种实验设置下实现较高的声纹识别率。

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