工业音频去噪的论文

以下是一篇关于工业音频去噪的论文：

标题：基于小波变换和深度学习的工业音频去噪算法

摘要：工业生产现场常常存在噪声干扰，这些噪声会严重影响工作质量和工人的健康。因此，开发一种有效的工业音频去噪算法至关重要。本文提出了一种基于小波变换和深度学习的工业音频去噪算法。首先，使用小波变换分解原始信号，然后通过深度卷积神经网络学习噪声和信号的特征表示，最后通过小波重建得到去噪信号。实验结果表明，本文提出的算法在工业噪声下具有较好的去噪效果，可有效提高音频质量和工作效率。

关键词：工业音频，去噪，小波变换，深度学习，卷积神经网络

Abstract: Industrial production sites often have noise interference, which can seriously affect work quality and workers' health. Therefore, it is important to develop an effective industrial audio denoising algorithm. This paper proposes an industrial audio denoising algorithm based on wavelet transform and deep learning. Firstly, the original signal is decomposed by wavelet transform, then the feature representation of noise and signal is learned by deep convolutional neural network, and finally the denoised signal is obtained by wavelet reconstruction. Experimental results show that the proposed algorithm has good denoising effect under industrial noise, which can effectively improve audio quality and work efficiency.

Keywords: industrial audio, denoising, wavelet transform, deep learning, convolutional neural networ