The paper is available in link.
sh run.sh or
$ conda create -n stgram_mfn python=3.7
$ conda activate stgram_mfn
$ pip install -r requirements.txt
$ python run.pyDCASE2020 Task2 Dataset:
data path can be set in config.yaml
Our trained model weights file for loading can be get in https://zenodo.org/record/7194640#.Y0t1WXZBxD8
| machine Type | AUC(%) | pAUC(%) | mAUC(%) |
|---|---|---|---|
| Fan | 94.04 | 88.97 | 81.39 |
| Pump | 91.94 | 81.75 | 83.48 |
| Slider | 99.55 | 97.61 | 98.22 |
| Valve | 99.64 | 98.44 | 98.83 |
| ToyCar | 94.44 | 87.68 | 83.07 |
| ToyConveyor | 74.57 | 63.60 | 64.16 |
| Average | 92.36 | 86.34 | 84.86 |
ToyCar
id AUC pAUC
1 0.830719697 0.652198679
2 0.951617251 0.874308413
3 0.995218329 0.981046957
4 0.99993531 0.999659526
Average 0.944372647 0.876803394
ToyConveyor
id AUC pAUC
1 0.869696875 0.766776316
2 0.641580986 0.547164566
3 0.725856264 0.594070052
Average 0.745711375 0.636003645
fan
id AUC pAUC
0 0.950638821 0.894607526
2 0.996852368 0.983433514
4 0.813936782 0.681034483
6 0.999972299 0.999854206
Average 0.940350067 0.889732432
pump
id AUC pAUC
0 0.892342657 0.744939271
2 0.83481982 0.693219535
4 0.9999 0.999473684
6 0.950490196 0.832301342
Average 0.919388168 0.817483458
slider
id AUC pAUC
0 1 1
2 0.982209738 0.906367041
4 0.99988764 0.999408634
6 0.999775281 0.998817268
Average 0.995468165 0.976148236
valve
id AUC pAUC
0 1 1
2 0.988333333 0.952192982
4 1 1
6 0.99725 0.985526316
Average 0.996395833 0.984429825
Total Average 0.923614376 0.863433498
If you think this work is useful to you, please cite:
@INPROCEEDINGS{9747868,
author={Liu, Youde and Guan, Jian and Zhu, Qiaoxi and Wang, Wenwu},
booktitle={ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={Anomalous Sound Detection Using Spectral-Temporal Information Fusion},
year={2022},
volume={},
number={},
pages={816-820},
doi={10.1109/ICASSP43922.2022.9747868}}