Unsupervised Anomaly Detection In Sound

Unsupervised sound anomaly detection is a method that automatically identifies and classifies abnormal sound signals using machine learning techniques. Its goal is to detect sound events that significantly deviate from normal patterns without the need for labeled data. This technology has significant application value in areas such as industrial equipment maintenance, environmental monitoring, and security alerts, enabling timely warnings of potential failures or anomalies and enhancing system reliability and safety.