L3DAS23: Learning 3D Audio Sources for Audio-Visual Extended Reality: ICASSP 2023

The L3DAS23 Challenge is aimed at encouraging and fostering collaborative research on machine learning for 3D audio signal processing, with a particular focus on 3D speech enhancement (SE) and 3D sound event localization and detection (SELD) in augmented reality applications. Alongside the challenge, we release the L3DAS23 dataset, a set of first-order Ambisonics recordings in reverberant simulated environments, accompanied by a Python API that facilitates the data usage and results submission stage. In the L3DAS22 Challenge, we introduced a novel multichannel audio configuration based on multiple-source and multiple-perspective Ambisonics recordings, performed with an array of two first-order Ambisonics microphones. For the L3DAS23 Challenge, we include additional visual information provided by pictures showing the frontal view from the microphone.

Visit the Challenge website for details and more information!