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@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", }