zenodoopen

Ground Truth for DCASE 2021 Challenge Task 2 Evaluation Dataset

Description This data is the ground truth for the "<a href="https://zenodo.org/record/4884786">evaluation dataset</a>" for the <a href="http://dcase.community/challenge2021/task-unsupervised-detection-of-anomalous-sounds">DCASE 2021 Challenge Task 2 "Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions"</a>.  In the task, three datasets have been released: "<a href="http://zenodo.org/record/4562016">development dataset</a>", "<a href="https://zenodo.org/record/4660992">additional training dataset</a>", and "<a href="https://zenodo.org/record/4884786">evaluation dataset</a>". The evaluation dataset was the last of the three released and includes around 200 samples for each machine type, section index, and domain, none of which have a condition label (i.e., normal or anomaly). This ground truth dataset contains the condition labels.   Data format The CSV file for each machine type, section index, and domain includes the ground truth data like the following: --------------------------------- section_03_source_test_0000.wav,1 section_03_source_test_0001.wav,1 ... section_03_source_test_0198.wav,0 section_03_source_test_0199.wav,1 --------------------------------- The first column shows the name of a wave file. The second column shows the condition label (i.e., 0: normal or 1: anomaly).   How to use A script for calculating the AUC, pAUC, precision, recall, and F1 scores for the "evaluation dataset" is available on the Github repository <a href="https://github.com/y-kawagu/dcase2021_task2_evaluator">[URL]</a>. The ground truth data are used by this system. For more information, please see the Github repository.   Conditions of use This dataset was created jointly by Hitachi, Ltd. and NTT Corporation and is available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license.   Publication If you use this dataset, please cite all the following three papers: <ul> <li>Yohei Kawaguchi, Keisuke Imoto, Yuma Koizumi, Noboru Harada, Daisuke Niizumi, Kota Dohi, Ryo Tanabe, Harsh Purohit, and Takashi Endo, "Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions," in arXiv e-prints: 2106.04492, 2021. [<a href="https://arxiv.org/abs/2106.04492">URL</a>]</li> <li>Noboru Harada, Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi, Masahiro Yasuda, Shoichiro Saito, "ToyADMOS2: Another Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection under Domain Shift Conditions," in arXiv e-prints: 2106.02369, 2021. [<a href="https://arxiv.org/abs/2106.02369">URL</a>]</li> <li>Ryo Tanabe, Harsh Purohit, Kota Dohi, Takashi Endo, Yuki Nikaido, Toshiki Nakamura, and Yohei Kawaguchi, "MIMII DUE: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection with Domain Shifts due to Changes in Operational and Environmental Conditions," in arXiv e-prints: 2105.02702, 2021. [<a href="https://arxiv.org/abs/2105.02702">URL</a>]</li> </ul> Feedback If there is any problem, please contact us: <ul> <li>Yohei Kawaguchi, <a href="mailto:yohei.kawaguchi.xk@hitachi.com">yohei.kawaguchi.xk@hitachi.com</a></li> <li>Daisuke Niizumi, <a href="mailto:daisuke.niizumi.dt@hco.ntt.co.jp">daisuke.niizumi.dt@hco.ntt.co.jp</a></li> <li>Keisuke Imoto, <a href="mailto:keisuke.imoto@ieee.org">keisuke.imoto@ieee.org</a></li> </ul>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship: 8
Harmonization: 8
Access: 12
Reuse readiness: 0
Engagement: 4

Topics

anomaly detection acoustic condition monitoring sound machine fault diagnosis machine learning unsupervised learning acoustic scene classification acoustic signal processing DCASE computational auditory scene analysis audio domain shift