Mechanical fault diagnosis is one of the important technologies in the fourth industrial
revolution. In recent years, mechanical fault diagnosis based on audio signal analysis …

Existing contrastive learning methods for anomalous sound detection refine the audio
representation of each audio sample by using the contrast between the samples' …

To ensure the reliable use and maintenance of a washing machine, condition monitoring
and detection of anomalous operations at an early stage are necessary. In this study, we …

Thanks to the development of deep learning, machine abnormal sound detection (MASD)
based on unsupervised learning has exhibited excellent performance. However, in the task …

Different machines can exhibit diverse frequency patterns in their emitted sound. This
feature has been recently explored in anomaly sound detection and reached state-of-the-art …

Anomalous Sound Detection (ASD) aims to identify whether the sound emitted from a
machine is anomalous or not. Most advanced methods use 2-D CNNs to extract features of …

Unsupervised anomalous sound detection by machines holds significant importance within
the realm of industrial automation. Currently, the task of machine-based anomalous sound …

This technical report describes our submission for DCASE 2023 challenge task 2. To
address the first-shot and domain shift problem in anomalous sound detection (ASD), we …

Although deep learning is the mainstream method in unsupervised anomalous sound
detection, Gaussian Mixture Model (GMM) with statistical audio frequency representation as …

For industrial anomalous sound detection (ASD), self-supervised methods have achieved
significant detection performance in many cases. Nevertheless, these methods typically rely …