Name
Title | ||
|---|---|---|
ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection |
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/WASPAA.2019.8937164 | 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) |
Keywords | Field | DocType |
Anomaly detection in sounds,machine operating sounds,product inspection,dataset | Signal processing,Computer vision,Anomaly detection,Product inspection,Sound detection,Computer science,Sampling (signal processing),Artificial intelligence,Acoustics | Conference |
ISSN | ISBN | Citations |
1931-1168 | 978-1-7281-1124-7 | 2 |
PageRank | References | Authors |
0.43 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Koizumi Yuma | 1 | 41 | 11.75 |
| Shoichiro Saito | 2 | 4 | 0.85 |
| Hisashi Uematsu | 3 | 2 | 1.10 |
| Harada Noboru | 4 | 67 | 25.07 |
| Keisuke Imoto | 5 | 27 | 9.27 |