Blind Separation of Delayed and Convolved Sources

Abstract

We address the difficult problem of separating multiple speakers with multiple microphones in a real room. We combine the work of Torkkola and Amari, Cichocki and Yang, to give Natural Gra(cid:173) dient information maximisation rules for recurrent (IIR) networks, blindly adjusting delays, separating and deconvolving mixed sig(cid:173) nals. While they work well on simulated data, these rules fail in real rooms which usually involve non-minimum phase transfer functions, not-invertible using stable IIR filters. An approach that sidesteps this problem is to perform infomax on a feedforward archi(cid:173) tecture in the frequency domain (Lambert 1996). We demonstrate real-room separation of two natural signals using this approach.

Cite

Text

Lee et al. "Blind Separation of Delayed and Convolved Sources." Neural Information Processing Systems, 1996.

Markdown

[Lee et al. "Blind Separation of Delayed and Convolved Sources." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/lee1996neurips-blind/)

BibTeX

@inproceedings{lee1996neurips-blind,
  title     = {{Blind Separation of Delayed and Convolved Sources}},
  author    = {Lee, Te-Won and Bell, Anthony J. and Lambert, Russell H.},
  booktitle = {Neural Information Processing Systems},
  year      = {1996},
  pages     = {758-764},
  url       = {https://mlanthology.org/neurips/1996/lee1996neurips-blind/}
}