Sketching for Nearfield Acoustic Imaging of Heavy-Tailed Sources

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10169)


We propose a probabilistic model for acoustic source localization with known but arbitrary geometry of the microphone array. The approach has several features. First, it relies on a simple nearfield acoustic model for wave propagation. Second, it does not require the number of active sources. On the contrary, it produces a heat map representing the energy of a large set of candidate locations, thus imaging the acoustic field. Second, it relies on a heavy-tail \(\alpha \)-stable probabilistic model, whose most important feature is to yield an estimation strategy where the multichannel signals need to be processed only once in a simple online procedure, called sketching. This sketching produces a fixed-sized representation of the data that is then analyzed for localization. The resulting algorithm has a small computational complexity and in this paper, we demonstrate that it compares favorably with state of the art for localization in realistic simulations of reverberant environments.


Candidate Location Direct Model Acoustic Model Microphone Array Steering Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partly supported by the research programme KAMoulox (ANR-15-CE38-0003-01) and EDiSon3D (ANR-13-CORD-0008-01) funded by ANR, the French State agency for research.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Inria, Speech Processing Team, Nancy Grand-EstNancyFrance
  2. 2.Institut Jean le Rond d’AlembertSaint-Cyr l’ÉcoleFrance
  3. 3.LTCI, CNRS, Télécom ParisTechUniversité Paris-SaclayParisFrance

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