The LOCATA challenge data corpus for acoustic source localization and tracking

Conference contribution
(Conference Contribution)

Publication Details

Author(s): Löllmann H, Evers C, Schmidt A, Mellmann H, Barfuß H, Naylor PA, Kellermann W
Editor(s): IEEE Signal Processing Society
Publication year: 2018
Pages range: 1-5
Language: English


Algorithms for acoustic source localization and tracking are essential for a wide range of applications such as personal assistants, smart homes, tele-conferencing systems, hearing aids, or autonomous systems. Numerous algorithms have been proposed for this purpose which, however, are not evaluated and compared against each other by using a common database so far.
The IEEE-AASP Challenge on sound source localization and tracking (LOCATA) provides a novel, comprehensive data corpus for the objective benchmarking of state-of-the-art algorithms on sound source localization and tracking.
The data corpus comprises six tasks ranging from the localization of a single static sound source with a static microphone array to the tracking of multiple moving speakers with a moving microphone array. It contains real-world multichannel audio recordings, obtained by hearing aids, microphones integrated in a robot head, a planar and a spherical microphone array in an enclosed acoustic environment, as well as positional information about the involved arrays and sound sources represented by moving human talkers or static loudspeakers.

FAU Authors / FAU Editors

Barfuß, Hendrik
Professur für Nachrichtentechnik
Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Löllmann, Heinrich Dr.-Ing.
Professur für Nachrichtentechnik
Schmidt, Alexander
Professur für Nachrichtentechnik

External institutions
Imperial College London / The Imperial College of Science, Technology and Medicine

How to cite

Löllmann, H., Evers, C., Schmidt, A., Mellmann, H., Barfuß, H., Naylor, P.A., & Kellermann, W. (2018). The LOCATA challenge data corpus for acoustic source localization and tracking. In IEEE Signal Processing Society (Eds.), (pp. 1-5). Sheffield, GB.

Löllmann, Heinrich, et al. "The LOCATA challenge data corpus for acoustic source localization and tracking." Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Sheffield Ed. IEEE Signal Processing Society, 2018. 1-5.


Last updated on 2018-16-10 at 12:53