Phase Unmixing : Multichannel Source Separation with Magnitude Constraints

Antoine Deleforge 1 Yann Traonmilin 1
1 PANAMA - Parcimonie et Nouveaux Algorithmes pour le Signal et la Modélisation Audio
Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
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.
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https://hal.inria.fr/hal-01372418
Contributor : Antoine Deleforge <>
Submitted on : Monday, March 13, 2017 - 5:24:15 PM
Last modification on : Thursday, November 15, 2018 - 11:59:00 AM
Document(s) archivé(s) le : Wednesday, June 14, 2017 - 3:13:53 PM

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  • HAL Id : hal-01372418, version 2
  • ARXIV : 1609.09744

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Antoine Deleforge, Yann Traonmilin. Phase Unmixing : Multichannel Source Separation with Magnitude Constraints. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017, New Orleans, United States. ⟨hal-01372418v2⟩

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