L3DAS22 - Rules

Rules and requirements

The goal of the challenge is to foster research on machinelearning for 3D audio. All participants should adhere to thefollowing rules to be eligible for the challenge:

  • All participants must submit the obtained results for at least one of the 2 tasks. The results should be accompanied by a paper describing the proposed method.
  • Each individual participant cannot be included in multiple participating teams. Therefore, a participant is allowed to submit only one set of results.
  • Winners will be selected according to the best performance for each single task, separately. Therefore, one winner for each task will be selected.
  • There are no restrictions on the proposed methodologies. However, in case of a tie, the Challenge Committee will take into account the novelty and originality of the proposed approach. Also, a method that can be used for both the 1-mic and 2-mic configurations will be positively evaluated.
  • Participants are not restricted to use the L3DAS22 dataset only. It is in fact allowed to augment this dataset and/or to integrate additional data to train/pre-train the models.
  • The Challenge can have up to 5 papers from the top ranked teams. The format should be consistent with ICASSP regular paper, and should be submitted before the camera-ready deadline.
  • Accepted papers will be presented at a Signal Processing Grand Challenge special session of the IEEE ICASSP 2022 conference. Authors, who are not interested in participating the challenge but want to make a contribution to the topic, are encouraged to submit a paper to this track, even without specifically use the proposed datasets.