Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU146638" target="_blank" >RIV/00216305:26220/22:PU146638 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0165168422004443" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0165168422004443</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.sigpro.2022.108905" target="_blank" >10.1016/j.sigpro.2022.108905</a>

Result language
angličtina
Original language name
Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization
Original language description
Audio inpainting, i.e., the task of restoring missing or occluded audio signal samples, usually relies on sparse representations or autoregressive modeling. In this paper, we propose to structure the spectrogram with nonnegative matrix factorization (NMF) in a probabilistic framework. First, we treat the missing samples as latent variables, and derive two expectation–maximization algorithms for estimating the parameters of the model, depending on whether we formulate the problem in the time- or time-frequency domain. Then, we treat the missing samples as parameters, and we address this novel problem by deriving an alternating minimization scheme. We assess the potential of these algorithms for the task of restoring short- to middle-length gaps in music signals. Experiments reveal great convergence properties of the proposed methods, as well as competitive performance when compared to state-of-the-art audio inpainting techniques.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20203 - Telecommunications

Project
<a href="/en/project/GA20-29009S" target="_blank" >GA20-29009S: Perceptually motivated restoration of highly degraded audio signals</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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