对称α稳定稀疏线性回归用于音乐音频去噪

N. Bassiou, Constantine Kotropoulos, Evangelia Koliopoulou
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引用次数: 14

摘要

提出了一种新的音乐音频去噪技术,该技术采用α-稳定分布对噪声进行建模。该方法基于具有结构化先验的稀疏线性回归,利用马尔可夫链蒙特卡罗推理估计干净信号模型参数和α-稳定噪声模型参数。对带有噪声的希腊民间音乐片段进行实验,结果表明,采用α-稳定噪声假设比采用高斯白噪声假设去噪效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Symmetric α-stable sparse linear regression for musical audio denoising
A new musical audio denoising technique is proposed, when the noise is modeled by an α-stable distribution. The proposed technique is based on sparse linear regression with structured priors and uses Markov Chain Monte Carlo inference to estimate the clean signal model parameters and the α-stable noise model parameters. Experiments on noisy Greek folk music excerpts demonstrate better denoising for the α-stable noise assumption than the Gaussian white noise one.
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