Application of Deep Neural Network Algorithm in Speech Enhancement of Online English Learning Platform

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2022-10-26 DOI:10.4108/eetsis.v10i1.2577

Haiyan Peng, Min Zhang

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引用次数: 1

Abstract

INTRODUCTION: In the online English learning platform, noise interference makes people unable to hear the content of English teaching clearly, which leads to a great reduction in the efficiency of English learning. In order to improve the voice quality of online English learning platform, the speech enhancement method of the online English learning platform based on deep neural network is studied.OBJECTIVES: This paper proposes a deep neural network-based speech enhancement method for online English learning platform in order to obtain more desirable results in the application of speech quality optimization.METHODS: The optimized VMD (Variable Modal Decomposition) algorithm is combined with the Moth-flame optimization algorithm to find the optimal solution to obtain the optimal value of the decomposition mode number and the penalty factor of the variational modal decomposition algorithm, and then the optimized variational modal decomposition algorithm is used to filter the noise information in the speech signal; Through the network speech enhancement method based on deep neural network learning, the denoised speech signal is taken as the enhancement target to achieve speech enhancement.RESULTS: The research results show that the method not only has significant denoising ability for speech signal, but also after this method is used, PESQ value of speech quality perception evaluation of speech signal is greater than 4.0dB, the spectral features are prominent, and the speech quality is improved.CONCLUSION: Through experiments from three perspectives: speech signal denoising, speech quality enhancement and speech spectrum information, the usability of the method in this paper is confirmed.

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深度神经网络算法在在线英语学习平台语音增强中的应用

导读:在在线英语学习平台中，噪音干扰使人们无法清晰地听到英语教学的内容，导致英语学习的效率大大降低。为了提高在线英语学习平台的语音质量，研究了基于深度神经网络的在线英语学习平台语音增强方法。目的:本文提出了一种基于深度神经网络的在线英语学习平台语音增强方法，以期在语音质量优化应用中获得更理想的效果。方法:将优化后的变模态分解(VMD)算法与Moth-flame优化算法相结合，寻找最优解，得到变分模态分解算法的分解模数和惩罚因子的最优值，然后利用优化后的变分模态分解算法对语音信号中的噪声信息进行滤波;通过基于深度神经网络学习的网络语音增强方法，将去噪后的语音信号作为增强目标，实现语音增强。结果:研究结果表明，该方法不仅对语音信号具有显著的去噪能力，而且使用该方法后，语音信号的语音质量感知评价PESQ值大于4.0dB，频谱特征突出，语音质量得到改善。结论:通过语音信号去噪、语音质量增强和语音频谱信息三个方面的实验，验证了本文方法的可用性。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.