Distribution Preserving Source Separation With Time Frequency Predictive Models

Pedro J. Villasana T., Janusz Klejsa, Lars Villemoes, Per Hedelin
3/10/2023
eess.AScs.LGcs.SD

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Abstract

We provide an example of a distribution preserving source separation method, which aims at addressing perceptual shortcomings of state-of-the-art methods. Our approach uses unconditioned generative models of signal sources. Reconstruction is achieved by means of mix-consistent sampling from a distribution conditioned on a realization of a mix. The separated signals follow their respective source distributions, which provides an advantage when separation results are evaluated in a listening test.

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Cite this paper

@article{t2023distribution,
  title  = {Distribution Preserving Source Separation With Time Frequency Predictive Models},
  author = {Pedro J. Villasana T. and Janusz Klejsa and Lars Villemoes and Per Hedelin},
  year   = {2023},
  eprint = {2303.05896},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.05896v1}
}

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