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 [BibTeX] [Marc21]
Euclidean Distance Matrix Completion for Ad-hoc Microphone Array Calibration
Type of publication: Conference paper
Citation: Taghizadeh_DSP_2013
Publication status: Published
Booktitle: Proceedings IEEE International Conference On Digital Signal Processing
Year: 2013
Month: July
Abstract: This paper addresses the application of missing data recovery via matrix completion for audio sensor networks. We propose a method based on Euclidean distance matrix completion for ad-hoc microphone array location calibration. This method can calibrate a full network from partial connectivity informa- tion. The pairwise distances of microphones in close proximity are estimated using the coherence model of the diffuse noise field. The distance matrix of the ad-hoc network is constructed where the distances of the microphones above a threshold are missing. We exploit the low-rank property of the squared distance matrix and apply a matrix completion method to recover the missing entries. In order to constrain the Euclidean space geometry, we propose the additional use of the Cadzow algorithm for matrix completion. The applicability of the proposed method is evaluated on real data recordings where a significant improvement over the state-of-the-art is achieved.
Keywords: Ad-hoc microphone calibration, Cadzow algorithm, Diffuse noise coherence, Matrix completion
Projects Idiap
Authors Taghizadeh, Mohammad J.
Parhizkar, Reza
Garner, Philip N.
Bourlard, Hervé
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Total mark: 0
  • Taghizadeh_DSP_2013.pdf