Ad-Hoc Microphone Array Calibration from Partial Distance Measurements

We address the problem of ad~hoc microphone array calibration where some of the distances between the microphones can not be measured. The conventional techniques require information about all the distances for accurate reconstruction of the array geometry. To alleviate this condition, we propose to exploit the properties of Euclidean distance matrices within the framework of low-rank matrix completion to recover the missing entries. We provide rigorous analysis to bound the calibration error using noisy measurements. This study elucidates the links between the performance and the structure of the missing distances, along with the size of the network. The experiments carried out on real data recordings demonstrate these theoretical insights. A significant improvement is achieved by the proposed Euclidean distance matrix completion algorithm over the state-of-the-art techniques for ad~hoc microphone array calibration.


Presented at:
Proceedings of the 4th Joint Workshop on Hands-free speech communication and Microphone Arrays
Year:
2014
Note:
Nominated for best paper award
Laboratories:




 Record created 2014-06-19, last modified 2018-03-17

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