Results 11 to 20 of about 3,234,615 (293)
EnergiesIndustrial anomalous sound detection is important for machine condition monitoring, especially when anomalous recordings are unavailable and only a small number of normal recordings can be collected from the target machine.
Pingdeng Shi +6 more
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Review of anomalous sound event detection approaches [PDF]
IAES International Journal of Artificial Intelligence (IJ-AI), 2019 <p>This paper presents a review of anomalous sound event detection(SED) approaches. SED is becoming more applicable for real-world appliactaions such as security, fire determination or olther emergency alarms. Despite many research outcome previously, further research is required to reduce false positives and improve accurracy.
Amirul Sadikin Md Afendi, Marina Yusoff
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Self-Supervised Learning for Anomalous Sound Detection
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)State-of-the-art anomalous sound detection (ASD) systems are often trained by using an auxiliary classification task to learn an embedding space. Doing so enables the system to learn embeddings that are robust to noise and are ignoring non-target sound events but requires manually annotated meta information to be used as class labels. However, the less
Wilkinghoff, Kevin
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ASD-Diffusion: Anomalous Sound Detection with Diffusion Models [PDF]
Unsupervised Anomalous Sound Detection (ASD) aims to design a generalizable method that can be used to detect anomalies when only normal sounds are given. In this paper, Anomalous Sound Detection based on Diffusion Models (ASD-Diffusion) is proposed for ASD in real-world factories.
Fengrun Zhang, Xiang Xie, Kai Guo
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Analysis of Feature Representations for Anomalous Sound Detection
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021 In this work, we thoroughly evaluate the efficacy of pretrained neural networks as feature extractors for anomalous sound detection. In doing so, we leverage the knowledge that is contained in these neural networks to extract semantically rich features (representations) that serve as input to a Gaussian Mixture Model which is used as a density ...
Robert Müller 0005 +3 more
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Sound Event Detection for Human Safety and Security in Noisy Environments
IEEE Access, 2022 The objective of a sound event detector is to recognize anomalies in an audio clip and return their onset and offset. However, detecting sound events in noisy environments is a challenging task. This is due to the fact that in a real audio signal several
Michael Neri +3 more
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IEEE Access, 2023 This paper proposes an anomalous sound detection (ASD) method that uses a combination of timbral metrics and short-term features tailored to industrial machine faults to identify whether the sound emitted from a target machine is anomalous.
Yasuji Ota, Masashi Unoki
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Journal of ICT Research and Applications, 2021 Anomaly detection in the sound from machines is an important task in machine monitoring. An autoencoder architecture based on the reconstruction error using a log-Mel spectrogram feature is a conventional approach for this domain. However, because of the
Hoang Van Truong +3 more
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Acoustic-Based Machine Condition Monitoring—Methods and Challenges
Eng, 2023 The traditional means of monitoring the health of industrial systems involves the use of vibration and performance monitoring techniques amongst others.
Gbanaibolou Jombo, Yu Zhang
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ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection [PDF]
2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2019 5 pages, to appear in IEEE WASPAA ...
Yuma Koizumi +4 more
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