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1 Télécom ParisTech - TSI LTCI - Laboratoire Traitement et Communication de l-Information

Abstract : Nonnegative Matrix Factorization NMF is a powerful tool for decomposing mixtures of audio signals in the Time-Frequency TF domain. In applications such as source separation, the phase recovery for each extracted component is a major issue since it often leads to audible artifacts. In this paper, we present a methodology for evaluating various NMF-based source separation techniques involving phase reconstruction. For each model considered, a comparison between two approaches blind separation without prior information and oracle separation with supervised model learning is performed, in order to inquire about the room for improvement for the estimation methods. Experimental results show that the High Resolution NMF HRNMF model is particularly promising, because it is able to take phases and correlations over time into account with a great expressive power.

Keywords : phase reconstruction Nonnegative matrix factorization time-frequency analysis audio source separation





Author: Paul Magron - Roland Badeau - Bertrand David -

Source: https://hal.archives-ouvertes.fr/



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