mlsanityData to 7 Oct 2026

Flow-based Self-supervised Density Estimation for Anomalous Sound Detection

arXiv 2103.08801 ↗First posted 16 Mar 2021eess.AS cs.LG cs.SDcited by 15

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Abstract (arXiv)

To develop a machine sound monitoring system, a method for detecting anomalous sound is proposed. Exact likelihood estimation using Normalizing Flows is a promising technique for unsupervised anomaly detection, but it can fail at out-of-distribution detection since the likelihood is affected by the smoothness of the data. To improve the detection performance, we train the model to assign higher likelihood to target machine sounds and lower likelihood to sounds from other machines of the same machine type. We demonstrate that this enables the model to incorporate a self-supervised classification-based approach. Experiments conducted using the DCASE 2020 Challenge Task2 dataset showed that the proposed method improves the AUC by 4.6% on average when using Masked Autoregressive Flow (MAF) and by 5.8% when using Glow, which is a significant improvement over the previous method.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 16 of its 23 references that are in the map. First posted on arXiv 16 Mar 2021.

Builds on

16 of 23 references.

References · 16

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  3. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,539
  4. 2014NICE: Non-linear Independent Components Estimationcited by 1,052
  5. 2018Deep Anomaly Detection with Outlier Exposurecited by 939
  6. 2017Masked Autoregressive Flow for Density Estimationcited by 680
  7. 2019Likelihood Ratios for Out-of-Distribution Detectioncited by 451
  8. 2018Do Deep Generative Models Know What They Don't Know?cited by 443
  9. 2020Why Normalizing Flows Fail to Detect Out-of-Distribution Datacited by 220
  10. 2019Input complexity and out-of-distribution detection with likelihood-based generative modelscited by 186
  11. 2020Understanding and Mitigating Exploding Inverses in Invertible Neural Networkscited by 71
  12. 2020Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoringcited by 43
4 more
  1. 2020Anomalous sound detection based on interpolation deep neural networkcited by 33
  2. 2020Anomaly Detection in Trajectory Data with Normalizing Flowscited by 11
  3. 2018AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translationcited by 7
  4. 2019Normalizing flows for novelty detection in industrial time series datacited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 5; 2024: 4; 2025: 2; 2026: 1.

15 papers.

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  1. 2022MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization Taskcited by 23
  2. 2021Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditionscited by 16
  3. 2023Self-Supervised Learning for Anomalous Sound Detectioncited by 8
  4. 2023Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretrainingcited by 7
  5. 2023Why do Angular Margin Losses work well for Semi-Supervised Anomalous Sound Detection?cited by 4
  6. 2023Noisy-ArcMix: Additive Noisy Angular Margin Loss Combined With Mixup Anomalous Sound Detectioncited by 3
  7. 2024Image-based Freeform Handwriting Authentication with Energy-oriented Self-Supervised Learningcited by 3
  8. 2024ASD-Diffusion: Anomalous Sound Detection with Diffusion Modelscited by 3
  9. 2022Anomalous Sound Detection Based on Machine Activity Detectioncited by 2
  10. 2023CSSL-RHA: Contrastive Self-Supervised Learning for Robust Handwriting Authenticationcited by 2
  11. 2024CoopASD: Cooperative Machine Anomalous Sound Detection with Privacy Concernscited by 1
  12. 2024Distributed collaborative anomalous sound detection by embedding sharingcited by 0
3 more
  1. 2025ESTM: An Enhanced Dual-Branch Spectral-Temporal Mamba for Anomalous Sound Detectioncited by 0
  2. 2025Noise Supervised Contrastive Learning and Feature-Perturbed for Anomalous Sound Detectioncited by 0
  3. 2026Sub-Band Spectral Matching with Localized Score Aggregation for Robust Anomalous Sound Detectioncited by 0