The challenge will consist of the following 6 tasks:
- Task 1: Localization of a single, static loudspeaker using static microphones arrays
- Task 2: Multi-source localization of static loudspeakers using static microphone arrays
- Task 3: Localization of a single, moving talker using static microphone arrays
- Task 4: Localization of multiple, moving talkers using static microphone arrays
- Task 5: Localization of a single, moving talker using moving microphone arrays
- Task 6: Multi-source localization of moving talkers using moving microphone arrays.
For scenarios 5 and 6, involving moving sensors, the position and orientation of the moving sensors will be made available to the participants. For scenarios 3 to 6, involving moving talkers, participants will be encouraged, but not limited to employ target tracking solutions in addition or in place of sound source localization approaches.
Four different microphone arrays haven been used for the measurements:
- Planar array with 15 channels (DICIT array) containing uniform linear sub-arrays
- Spherical array with 32 channels (Eigenmike)
- Pseudo-spherical array with 12-channels (robot head)
- Hearing aid dummies on a dummy head (2-channel per hearing aid).
- Development data set: Contains multichannel audio recordings and ground truth data for the all microphone positions and source positions.
- Evaluation data set: Contains multichannel audio recordings and ground truth data for the microphone positions.
Participants of the challenge can submit results to a single or several challenge tasks using a single or several microphone configurations.
Evaluation Measures and System
An optical tracking system (OptiTrack) was used to record the positions and orientations of talker, loudspeakers and microphone arrays. The ground truth values will be compared to the estimated locations submitted by the participants using several criteria to evaluate the variance with different talkers and the accuracy of the estimated locations. Furthermore, an attempt will be made to assess the relative computational complexity of the algorithms by considering the programming/scripting language (MATLAB, C++ etc.), processing units, and execution time.