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

This paper proposes a novel optimization principle and its implementation for unsupervised anomaly detection in sound (ADS) using an autoencoder (AE). The goal of the unsupervised-ADS is to detect unknown anomalous sounds without training data of anomalous sounds. The use of an AE as a normal model...

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