We present the task description of the Detection and Classification of Acoustic Scenes and
Events (DCASE) 2023 Challenge Task 2:``First-shot unsupervised anomalous sound …

Anomaly detection through machine sounds plays a crucial role in the development of
industrial automation due to its excellent flexibility and real-time response capabilities …

State-of-the-art anomalous sound detection (ASD) systems are often trained by using an
auxiliary classification task to learn an embedding space. Doing so enables the system to …

Anomalous Sound Detection (ASD) has gained significant interest through the application of
various Artificial Intelligence (AI) technologies in industrial settings. Though possessing …

First-shot (FS) unsupervised anomalous sound detection (ASD) is a brand-new task
introduced in DCASE 2023 Challenge Task 2, where the anomalous sounds for the target …

Large pre-trained models have demonstrated dominant performances in multiple areas,
where the consistency between pre-training and fine-tuning is the key to success. However …

In contrast to human speech, machine-generated sounds of the same type often exhibit
consistent frequency characteristics and discernible temporal periodicity. However …

In the previous Detection and Classification of Acoustic Scenes and Events (DCASE)
Challenge Task 2: Anomalous Sound Detection (ASD) for Machine Condition Monitoring …

Machine anomalous sound detection (ASD) has emerged as one of the most promising
applications in the Industrial Internet of Things (IIoT) due to its unprecedented efficacy in …

This report presents our work for DCASE 2024 Task 2: first shot unsupervised anomalous
sound detection for machine condition monitoring. This year's challenge is heightened by …