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.
Type de document :
Communication dans un congrès
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Mar 2017, New Orleans, United States. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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https://hal.inria.fr/hal-01372418
Contributeur : Antoine Deleforge <>
Soumis le : lundi 13 mars 2017 - 17:24:15
Dernière modification le : mardi 21 novembre 2017 - 15:23:52
Document(s) archivé(s) le : mercredi 14 juin 2017 - 15:13:53

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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. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 〈hal-01372418v2〉

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