High resolution NMF for modeling mixtures of non-stationary signals in the time-frequency domain
Résumé
Nonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixtures of non-stationary signals in the Time-Frequency (TF) domain. However, unlike the High Resolution (HR) methods dedicated to mixtures of complex exponentials, its spectral resolution is limited by that of the underlying TF representation. In this paper, we present a unified probabilistic model called HR-NMF, that permits to overcome this limit by taking both phases and local correlations in each frequency band into account. This model is estimated with a recursive implementation of the Expectation-Maximization (EM) algorithm. Its capabilities are illustrated in the context of audio source separation and audio inpainting.
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