Complex NMF under phase constraints based on signal modeling: application to audio source separation

Paul Magron (1, 2) , Roland Badeau (2, 1) , Bertrand David (1, 2)

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

Nonnegative Matrix Factorization (NMF) is a powerful tool for de- composing mixtures of audio signals in the Time-Frequency (TF) domain. In the source separation framework, the phase recovery for each extracted component is necessary for synthesizing time-domain signals. The Complex NMF (CNMF) model aims to jointly estimate the spectrogram and the phase of the sources, but requires to con- strain the phase in order to produce satisfactory sounding results. We propose to incorporate phase constraints based on signal models within the CNMF framework: a phase unwrapping constraint that enforces a form of temporal coherence, and a constraint based on the repetition of audio events, which models the phases of the sources within onset frames. We also provide an algorithm for estimating the model parameters. The experimental results highlight the interest of including such constraints in the CNMF framework for separating overlapping components in complex audio mixtures.

Mots clés: source separation; repeated audio events; phase unwrapping; phase recovery; Nonnegative matrix factorization

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Paul Magron, Roland Badeau, Bertrand David. Complex NMF under phase constraints based on signal modeling: application to audio source separation. 41st International Conference on Acoustics, Speech and Signal Processing (ICASSP.2016)), Mar 2016, Shanghai, China. ⟨hal-01248013⟩