Unsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson Lemma

Yuma Koizumi, Shoichiro Saito, Hisashi Uematsum Yuta Kawachi +1

This paper proposes a novel optimization principle and its implementation for unsupervised anomaly detection in sound (ADS) using an autoencoder (AE). The goal of unsupervised-ADS…