000256322 001__ 256322
000256322 005__ 20190125163145.0
000256322 037__ $$aCONF
000256322 245__ $$aAd-Hoc Microphone Array Calibration from Partial Distance Measurements
000256322 260__ $$c2014
000256322 269__ $$a2014
000256322 336__ $$aConference Papers
000256322 520__ $$aWe 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
000256322 700__ $$aTaghizadeh, Mohammad J.
000256322 700__ $$aAsaei, Afsaneh
000256322 700__ $$aGarner, Philip N.
000256322 700__ $$aBourlard, Hervé
000256322 7112_ $$aProceeding of 4th Joint Workshop on Hands-free Speech Communication and Microphone Arrays
000256322 909C0 $$zMarselli, Béatrice$$mfrank.formaz@epfl.ch$$xU10381
000256322 909CO $$pconf$$pSTI$$ooai:infoscience.epfl.ch:256322
000256322 909C0 $$0252189$$pLIDIAP
000256322 970__ $$aTaghizadeh_HSCMA_2014/IDIAP
000256322 973__ $$aEPFL
000256322 980__ $$aCONF
000256322 980__ $$aLIDIAP_test