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We present the task description and discussion on the results of the DCASE 2021 Challenge Task 2.
Y. Koizumi, S. Saito, H. Uematsu, and N. Harada, “Optimizing acoustic feature extractor for anomalous sound detection based on Neyman-Pearson lemma,” in
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Y. Koizumi, S. Saito, H. Uematsu, Y. Kawachi, and N. Harada, “Unsupervised detection of anomalous sound based on deep learning and the Neyman-Pearson lemma,”
2019
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Y. Kawaguchi, R. Tanabe, T. Endo, K. Ichige, and K. Hamada, “Anomaly detection based on an ensemble of dereverberation and anomalous sound extraction,” in
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Y. Koizumi, S. Saito, M. Yamaguchi, S. Murata, and N. Harada, “Batch uniformization for minimizing maximum anomaly score of DNN-based anomaly detection in sounds,” in
2019
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D. Hendrycks, M. Mazeika, and T. G. Dietterich, “Deep anomaly detection with outlier exposure,” in
2019
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K. Suefusa, T. Nishida, H. Purohit, R. Tanabe, T. Endo, and Y. Kawaguchi, “Anomalous sound detection based on interpolation deep neural network,” in
2020
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H. Purohit, R. Tanabe, T. Endo, K. Suefusa, Y. Nikaido, and Y. Kawaguchi, “Deep autoencoding GMM-based unsupervised anomaly detection in acoustic signals and its hyper-parameter optimization,” in
2020
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Y. Koizumi, Y. Kawaguchi, K. Imoto, T. Nakamura, Y. Nikaido, R. Tanabe, H. Purohit, K. Suefusa, T. Endo, M. Yasuda, and N. Harada, “Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring,” in
2020
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R. Giri, S. V. Tenneti, F. Cheng, K. Helwani, U. Isik, and A. Krishnaswamy, “Self-supervised classification for detecting anomalous sounds,” in
2020
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S. Kapka, “ID-conditioned auto-encoder for unsupervised anomaly detection,” in
2020
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P. Primus, V. Haunschmid, P. Praher, and G. Widmer, “Anomalous sound detection as a simple binary classification problem with careful selection of proxy outlier examples,” in
2020
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T. Inoue, P. Vinayavekhin, S. Morikuni, S. Wang, T. H. Trong, D. Wood, M. Tatsubori, and R. Tachibana, “Detection of anomalous sounds for machine condition monitoring using classification confidence,” in
2020
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Q. Zhou, “ArcFace based sound MobileNets for DCASE 2020 task 2,” DCASE2020 Challenge, Tech. Rep., 2020
2020
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J. Lopez, L. Hong, P. Lopez-Meyer, L. Nachman, G. Stemmer, and J. Huang, “A speaker recognition approach to anomaly detection,” DCASE2020 Challenge, Tech. Rep., 2020
2020
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K. Wilkinghoff, “Anomalous sound detection with Look, Listen, and Learn embeddings,” DCASE2020 Challenge, Tech. Rep., 2020
J. Lopez, G. Stemmer, and P. Lopez-Meyer, “Ensemble of complementary anomaly detectors under domain shifted conditions,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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K. Morita, T. Yano, and K. Tran, “Anomalous sound detection using CNN-based features by self supervised learning,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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K. Wilkinghoff, “Utilizing sub-cluster AdaCos for anomalous sound detection under domain shifted conditions,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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I. Kuroyanagi, T. Hayashi, Y. Adachi, T. Yoshimura, K. Takeda, and T. Toda, “Anomalous sound detection with ensemble of autoencoder and binary classification approaches,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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Y. Sakamoto and N. Miyamoto, “Combine Mahalanobis distance, interpolation auto encoder and classification approach for anomaly detection,” DCASE2021 Challenge, Tech. Rep., 2021
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2020
Cited alongside, same era.
Z. Shinmura, “DCASE2020 task2 self-supervised learning solution,” DCASE2020 Challenge, Tech. Rep., 2020
2020
Cited alongside, same era.
Q. Wei and Y. Liu, “Auto-encoder and metric-learning for anomalous sound detection task,” DCASE2020 Challenge, Tech. Rep., 2020
2020
Cited alongside, same era.
F. Ahmed, P. Nguyen, and A. Courville, “An ensemble approach for detecting machine failure from sound,” DCASE2020 Challenge, Tech. Rep., 2020
2020
Cited alongside, same era.
Y. Xiao, “Unsupervised detection of anomalous sounds technical report,” DCASE2020 Challenge, Tech. Rep., 2020
2020
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Closest in time.
Q. Zhou, “Ensemble of ArcFace based systems for unsupervised anomalous sound detection under domain shift conditions,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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Y. Wang, Y. Zheng, Y. Zhang, and L. He, “Several approaches for anomaly detection from sound,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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J. Tozicka, D. Karel, and L. Michal, “Unsupervised anomalous sound detection by Siamese network and auto-encoder,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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X. Cai, H. Dinkel, Z. Yan, Y. Wang, J. Zhang, and Y. Wang, “The small rice camera ready submission to the dcase2021: Semi-supervised anomaly detection using contrastive learning,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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H. Narita and A. Tamamori, “Unsupervised anomalous sound detection using intermediate representation of trained models and metric learning based variational autoencoder,” DCASE2021 Challenge, Tech. Rep., 2021
2021
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K. Dohi, T. Endo, H. Purohit, R. Tanabe, and Y. Kawaguchi, “Flow-based self-supervised density estimation for anomalous sound detection,” in
2021
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