Symmetric α-table Sparse Linear Regression for Musical Audio Denoising

被引：0

作者：

Bassiou, Nikoletta ^{[1
]}

Kotropoulos, Constantine ^{[1
]}

Koliopoulou, Evangelia ^{[1
]}

机构：

[1] Aristotle Univ Thessaloniki, Dept Informat, Thessaloniki 54124, Greece

来源：

2013 8TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (ISPA) | 2013年

关键词：

DISTRIBUTIONS; INFERENCE;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A new musical audio denoising technique is proposed, when the noise is modeled by an alpha-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 alpha-stable noise model parameters. Experiments on noisy Greek folk music excerpts demonstrate better denoising for the alpha-stable noise assumption than the Gaussian white noise one.

引用

页码：382 / 387

页数：6

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