Phase Unmixing : Multichannel Source Separation with Magnitude Constraints
Abstract
We consider the problem of estimating the phases of K mixed complex signals from a multichannel observation, when the mixing matrix and signal magnitudes are known. This problem can be cast as a non-convex quadratically constrained quadratic program which is known to be NP-hard in general. We propose three approaches to tackle it: a heuristic method, an alternate minimization method, and a convex relaxation into a semi-definite program. The last two approaches are showed to outperform the oracle multichannel Wiener filter in under-determined informed source separation tasks, using simulated and speech signals. The convex relaxation approach yields best results, including the potential for exact source separation in under-determined settings.
Cite
@article{arxiv.1609.09744,
title = {Phase Unmixing : Multichannel Source Separation with Magnitude Constraints},
author = {Antoine Deleforge and Yann Traonmilin},
journal= {arXiv preprint arXiv:1609.09744},
year = {2017}
}
Comments
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017, New Orleans, United States