论文标题
L3DAS22挑战：在真实办公环境中学习3D音频源
L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment
论文作者
论文摘要
L3DAS22挑战旨在鼓励制定机器学习策略，以增强3D语音，并在类似办公室的环境中进行3D声音本地化和检测。此挑战改善并扩展了L3DAS21版的任务。我们生成了一个新的数据集，该数据集维持L3DAS21数据集的相同一般特征，但是数据点延长并增加了约束，以提高基线模型的效率，并克服了先前挑战参与者遇到的主要困难。我们使用上一个挑战版中排名第一的体系结构更新了任务1的基线模型。我们撰写了新的支持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。
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.
