IEEE MLSP Data Challenge 2021
L3DAS21
Machine Learning for 3D Audio Signal Processing
Scope of the Challenge
The L3DAS21 Challenge for the IEEE MLSP 2021 aims at encouraging and fostering research on machine learning for 3D audio signal processing. In multi-speaker scenarios it is very important to properly understand the nature of a sound event and its position within the environment, what is the content of the sound signal and how to leverage it at best for a specific application (e.g., teleconferencing rather than assistive listening or entertainment, among others). To this end, L3DAS21 Challenge presents two tasks: 3D Speech Enhancement and 3D Sound Event Localization and Detection, both relying on first-order Ambisonics recordings in reverberant office environment.
Each task involves 2 separate tracks: 1-mic and 2-mic recordings, respectively containing sounds acquired by one Ambisonics microphone and by an array of two Ambisonics microphones. The use of two first-order Ambisonics microphones definitely represents one of the main novelties of the L3DAS21 Challenge.
- Task 2: 3D Sound Event Localization and Detection
The aim of this task is to detect the temporal activities of a known set of sound event classes and, in particular, to further locate them in the space.Here the models must predict a list of the active sound events and their respective location at regular intervals of 100 milliseconds. Performance on this task is evaluated according to the location-sensitive detection error, which joins the localization and detection errors.
Besides submitting papers related to L3DAS21 Challenge, authors are encouraged to submit to this special session also papers related to the topic of machine learning for 3D audio signal processing.
Timeline
- 27 Mar 2021 ? Release of the training and development sets
- 10 May 2021 ? Release of the evaluation test set
- 20 May 2021 ? Deadline for submitting results for both tasks
- 25 Oct 2021 ? Opening of the IEEE Workshop on MLSP 2021
Challenge Website and Contacts
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