We present the task description of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2022 Challenge Task 2: "Unsupervised anomalous sound detection (ASD) for machine condition monitoring applying domain generalization techniques". Domain shifts are a critical problem for the application of ASD systems. Because domain shifts can change the acoustic characteristics of data, a model trained in a source domain performs poorly for a target domain. In DCASE 2021 Challenge Task 2, we organized an ASD task for handling domain shifts. In this task, it was assumed that the occurrences of domain shifts are known. However, in practice, the domain of each sample may not be given, and the domain shifts can occur implicitly. In 2022 Task 2, we focus on domain generalization techniques that detects anomalies regardless of the domain shifts. Specifically, the domain of each sample is not given in the test data and only one threshold is allowed for all domains. We will add challenge results and analysis of the submissions after the challenge submission deadline.

翻译：我们介绍了2022年声学场景和事件的探测和分类(DCASE)任务说明:任务2:“在应用领域通用技术进行机器状况监测时,不受监督的异常声音探测(ASD)”,域变换是应用ASD系统的一个关键问题。由于域变换可以改变数据的声学特征,在源域中受过训练的模型在目标域中表现不佳。在DCASE 2021 挑战任务2中,我们安排了处理域变换的ASD任务。在这项任务中,我们假定域变换的发生是已知的。但在实践中,可能没有提供每个样本的域,而域变换可能暗地发生。在2022年任务2中,我们侧重于发现异常的域变技术,而不论域变换,具体地说,每个样品的域不在试验数据中给出,所有域只允许一个阈值。我们将在提交挑战截止日期后添加对所提交文件的挑战结果和分析。