Machine Anomalous Sound Detection Based on Feature Fusion and Gaussian Mixture Model

Author:

Cai Shengqiang,Zhou Wenju,Ren Xinzhen

Publisher

Springer Nature Singapore

Reference20 articles.

1. Koizumi, Y., Kawaguchi, Y., Imoto, K., Nakamura, T., Nikaido, Y., Tanabe, R., et al.: Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring. In: Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCASE2020), pp. 81–85 (2020)

2. Ruff, L., et al.: A unifying review of deep and shallow anomaly detection. Proc. IEEE 2021(109), 756–95 (2021)

3. Daniluk, P., Gozdziewski, M., Kapka, S., Kosmider, M.: Ensemble of auto-encoder based systems for anomaly detection. Technical report, DCASE2020 Challenge (2020)

4. Kapka, S.: ID-conditioned auto-encoder for unsupervised anomaly detection. In: Detection and Classification of Acoustic Scenes and Events Workshop (DCASE), pp. 71–75 (2020)

5. Suefusa, K., Nishida, T., Purohit, H., Tanabe, R., Endo, T., Kawaguchi, Y.: Anomalous sound detection based on interpolation deep neural network. In: ICASSP 2020–2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, pp. 271–275 (2020)

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