Description and discussion on DCASE 2021 challenge task 2: Unsupervised anomalous sound detection for machine condition monitoring under domain shifted …
We present the task description and discussion on the results of the DCASE 2021 Challenge
Task 2. In 2020, we organized an unsupervised anomalous sound detection (ASD) task …
Task 2. In 2020, we organized an unsupervised anomalous sound detection (ASD) task …
Why do angular margin losses work well for semi-supervised anomalous sound detection?
State-of-the-art anomalous sound detection systems often utilize angular margin losses to
learn suitable representations of acoustic data using an auxiliary task, which usually is a …
learn suitable representations of acoustic data using an auxiliary task, which usually is a …
Self-supervised representation learning for unsupervised anomalous sound detection under domain shift
H Chen, Y Song, LR Dai… - ICASSP 2022-2022 …, 2022 - ieeexplore.ieee.org
In this paper, a self-supervised representation learning method is proposed for anomalous
sound detection (ASD). ASD has received much research attention in recent DCASE …
sound detection (ASD). ASD has received much research attention in recent DCASE …
Outlier-aware inlier modeling and multi-scale scoring for anomalous sound detection via multitask learning
Y Zhang, H Suo, Y Wan, M Li - arxiv preprint arxiv:2309.07500, 2023 - arxiv.org
This paper proposes an approach for anomalous sound detection that incorporates outlier
exposure and inlier modeling within a unified framework by multitask learning. While outlier …
exposure and inlier modeling within a unified framework by multitask learning. While outlier …
An effective anomalous sound detection method based on representation learning with simulated anomalies
In this paper, we propose an effective anomalous sound detection (ASD) method based on
representation learning with simulated anomalies. Recently, ASD systems have used Outlier …
representation learning with simulated anomalies. Recently, ASD systems have used Outlier …
SSDPT: Self-supervised dual-path transformer for anomalous sound detection
Anomalous sound detection for machine condition monitoring or structural health monitoring
is essential in the development of Industry 4.0. However, the anomalous sounds of …
is essential in the development of Industry 4.0. However, the anomalous sounds of …
Anomalous sound detection based on machine activity detection
We have developed an unsupervised anomalous sound detection method for machine
condition monitoring that utilizes an auxiliary task-detecting when the target machine is …
condition monitoring that utilizes an auxiliary task-detecting when the target machine is …
SW-WAVENET: learning representation from spectrogram and WaveGram using WaveNet for anomalous sound detection
H Chen, L Ran, X Sun, C Cai - ICASSP 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Anomalous Sound Detection (ASD) aims to identify whether the sound emitted from a
machine is anomalous or not. Most advanced methods use 2-D CNNs to extract features of …
machine is anomalous or not. Most advanced methods use 2-D CNNs to extract features of …
[PDF][PDF] Thuee system for first-shot unsupervised anomalous sound detection for machine condition monitoring
This report presents our work for DCASE 2023 Task 2: firstshot unsupervised anomalous
sound detection for machine condition monitoring. This task mainly focuses on first-shot …
sound detection for machine condition monitoring. This task mainly focuses on first-shot …
Improvement of serial approach to anomalous sound detection by incorporating two binary cross-entropies for outlier exposure
Anomalous sound detection systems must detect unknown, atypical sounds using only
normal audio data. Conventional methods use the serial method, a combination of outlier …
normal audio data. Conventional methods use the serial method, a combination of outlier …