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@conference{c6964b83e2c746ae915acd8e763b9eed, author = "Paul Magron and Tuomas Virtanen", abstract = "In this paper, we study statistical models for the phase of the short-term Fourier transform (STFT) of audio signals. STFT phase globally appears as uniformly distributed, which has led researchers in this field to model it as a uniform random variable. However, some information about the phase can be obtained from a sinusoidal model, which reveals its local structure. Therefore, we propose to model the phase with a von Mises (VM) random variable, which enables us to favor the sinusoidal model-based phase value. We estimate the distribution parameters and we validate this model on real audio data. In particular, we observe that both models (uniform and VM) are relevant from a statistical perspective but they convey different information about the phase (global vs. local). We also apply this VM model to an audio source separation task, where it outperforms previous approaches.", booktitle = "16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018", day = "2", doi = "10.1109/IWAENC.2018.8521323", keywords = "source separation", month = "11", publisher = "IEEE", title = "{O}n modeling the {STFT} phase of audio signals with the von {M}ises distribution", year = "2018", }