Greek Folk Music Denoising Under a Symmetric α-Stable Noise Assumption

Nikoletta Bassiou, Constantine Kotropoulos, Ioannis Pitas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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153 Downloads (Pure)

Abstract

The noise in musical audio recordings is assumed to obey an α-stable distribution. A sparse linear regression framework with structured priors is elaborated. Markov Chain Monte Carlo is used to infer the clean music signal model and the α-stable noise distribution parameters. The musical audio recordings are processed both as a whole and in segments by using a sine-bell window for analysis and overlap-and-add reconstruction. Experiments on noisy Greek folk music excerpts demonstrate better denoising under the α-stable noise assumption than the Gaussian white noise one, and when processing is performed in segments rather than in full recordings.
Original languageEnglish
Title of host publication2014 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine 2014)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages18-23
Number of pages6
ISBN (Print)9781509000111
DOIs
Publication statusPublished - 18 Aug 2014
Event10th International Conference Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE 2014 - Rhodes, Greece
Duration: 18 Aug 201420 Aug 2014

Conference

Conference10th International Conference Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE 2014
CountryGreece
CityRhodes
Period18/08/1420/08/14

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