Blind Source Separation with Optimal Transport Non-negative Matrix Factorization

@article{Rolet2018BlindSS,
  title={Blind Source Separation with Optimal Transport Non-negative Matrix Factorization},
  author={Antoine Rolet and Vivien Seguy and Mathieu Blondel and Hiroshi Sawada},
  journal={CoRR},
  year={2018},
  volume={abs/1802.05429}
}
Optimal transport as a loss for machine learning optimization problems has recently gained a lot of attention. Building upon recent advances in computational optimal transport, we develop an optimal transport non-negative matrix factorization (NMF) algorithm for supervised speech blind source separation (BSS). Optimal transport allows us to design and leverage a cost between short-time Fourier transform (STFT) spectrogram frequencies, which takes into account how humans perceive sound. We give… CONTINUE READING