DocumentCode :
669207
Title :
Symmetric α-stable sparse linear regression for musical audio denoising
Author :
Bassiou, Nikoletta ; Kotropoulos, Constantine ; Koliopoulou, Evangelia
Author_Institution :
Dept. of Inf., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece
fYear :
2013
fDate :
4-6 Sept. 2013
Firstpage :
382
Lastpage :
387
Abstract :
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.
Keywords :
Gaussian noise; Markov processes; Monte Carlo methods; audio signal processing; music; parameter estimation; regression analysis; signal denoising; statistical distributions; α-stable distribution; α-stable noise assumption; α-stable noise model parameter; Gaussian white noise; Markov chain Monte Carlo inference; clean signal model parameter estimation; musical audio denoising technique; noisy Greek folk music excerpts; structured priors; symmetric α-stable sparse linear regression; Mathematical model; Noise; Noise measurement; Noise reduction; Signal processing algorithms; Transient analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing and Analysis (ISPA), 2013 8th International Symposium on
Conference_Location :
Trieste
Type :
conf
DOI :
10.1109/ISPA.2013.6703771
Filename :
6703771
Link To Document :
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