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ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection

2019-08-09 03:52:08
Yuma Koizumi, Shoichiro Saito, Hisashi Uematsu, Noboru Harada, Keisuke Imoto

Abstract

This paper introduces a new dataset called "ToyADMOS" designed for anomaly detection in machine operating sounds (ADMOS). To the best our knowledge, no large-scale datasets are available for ADMOS, although large-scale datasets have contributed to recent advancements in acoustic signal processing. This is because anomalous sound data are difficult to collect. To build a large-scale dataset for ADMOS, we collected anomalous operating sounds of miniature machines (toys) by deliberately damaging them. The released dataset consists of three sub-datasets for machine-condition inspection, fault diagnosis of machines with geometrically fixed tasks, and fault diagnosis of machines with moving tasks. Each sub-dataset includes over 180 hours of normal machine-operating sounds and over 4,000 samples of anomalous sounds collected with four microphones at a 48-kHz sampling rate. The dataset is freely available for download at https://github.com/YumaKoizumi/ToyADMOS-dataset

Abstract (translated)

URL

https://arxiv.org/abs/1908.03299

PDF

https://arxiv.org/pdf/1908.03299


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