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A Compressive Sensing Method for Noise Reduction of Speech and Audio Signals

机译：一种语音和音频信号降噪的压缩传感方法

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摘要

Recently, compressive sensing (CS) has been intensively studied in the fields of applied mathematics and signal processing. However, its application to speech processing has not been well discussed. In this paper, we propose a compressive sensing method for noise reduction of speech and audio signals. The noise reduction problem is formulated in the theoretical framework of CS, as an l_1-minimisation problem with a linear combination of a constrained term, by adopting a random partial Fourier transform operator. Furthermore, a gradient descend line search (GDLS) algorithm is adopted to efficiently solve the optimisation problem. Finally, we demonstrate that the proposed method is quite effective in reducing the noise of speech signals, especially for stationary and nonstationary white Gaussian noises.
机译：最近，在应用数学和信号处理领域中已经集中研究了压缩感应（CS）。但是，它对语音处理的应用尚未讨论。在本文中，我们提出了一种用于语音和音频信号的降噪的压缩感测方法。通过采用随机部分傅立叶变换操作员，在CS的理论框架中配制在CS的理论框架中，作为L_1 - 最小化问题，通过采用随机部分傅里叶变换操作员。此外，采用梯度下降线搜索（GDLS）算法以有效解决优化问题。最后，我们证明该方法在降低语音信号的噪声方面非常有效，特别是对于静止和非间断的白色高斯噪声。

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