The L3DAS22 Challenge is aimed at encouraging the development of machine learning strategies for 3D speech enhancement and 3D sound localization and detection in office-like environments. This challenge improves and extends the tasks of the L3DAS21 edition. We generated a new dataset, which maintains the same general characteristics of L3DAS21 datasets, but with an extended number of data points and adding constrains that improve the baseline model's efficiency and overcome the major difficulties encountered by the participants of the previous challenge. We updated the baseline model of Task 1, using the architecture that ranked first in the previous challenge edition. We wrote a new supporting API, improving its clarity and ease-of-use. In the end, we present and discuss the results submitted by all participants. L3DAS22 Challenge website: www.l3das.com/icassp2022.

翻译：L3DAS22挑战旨在鼓励制定3D语音增强和3D声音定位的机器学习战略,并在类似办公室的环境中探测和探测3D声音定位,这一挑战改进并扩大了L3DAS21版的任务范围,我们产生了一个新的数据集,该数据集保持L3DAS21数据集的一般特点,但数据点数量更多,增加了提高基线模型效率和克服前一个挑战参与者遇到的主要困难的限制因素。我们利用前一个挑战版排名第一的结构更新了任务1的基准模型。我们编写了一份新的支持性API,提高了其清晰度和易用性。最后,我们介绍并讨论所有参与者提交的结果。L3DAS22挑战网站:www.l3das.com/icassp2022。