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/}
}