@conference{b3668c158a0044079ec125e63cf4b218,
author = "Paul Magron and Tuomas Virtanen",
abstract = "Complex nonnegative matrix factorization (NMF) is a powerful tool for decomposing audio spectrograms while accounting for some phase information in the time-frequency domain. While its estimation was originally based on the Euclidean distance, in this paper we propose to extend it to any beta-divergence, a family of functions widely used in audio to estimate NMF. To this end, we introduce the beta-divergence in a heuristic fashion within a phase-aware probabilistic model. Estimating this model results in performing an NMF with Itakura-Saito (IS) divergence on a quantity called the phase-corrected posterior power of the sources, which is both phase-dependent and nonnegative-valued. Therefore, we replace IS with the beta-divergence, so that the factorization uses an optimal distortion metric and remains phase-aware. Even though by doing so we loose theoretical convergence guarantees, the resulting algorithm demonstrates its potential for an audio source separation task, where it outperforms previous complex NMFs approaches.",
booktitle = "2018 16th International Workshop on Acoustic Signal Enhancement (IWAENC)",
doi = "10.1109/IWAENC.2018.8521317",
isbn = "978-1-5386-8152-7",
keywords = "source separation",
month = "9",
pages = "156--160",
publisher = "IEEE",
title = "{T}owards {C}omplex {N}onnegative {M}atrix {F}actorization with the {B}eta-{D}ivergence",
year = "2018",
}