A decade of DCASE: Achievements, practices, evaluations and future challenges
A Mesaros, R Serizel, T Heittola, T Virtanen… - arxiv preprint arxiv …, 2024 - arxiv.org
This paper introduces briefly the history and growth of the Detection and Classification of
Acoustic Scenes and Events (DCASE) challenge, workshop, research area and research …
Acoustic Scenes and Events (DCASE) challenge, workshop, research area and research …
Planing It by Ear: Convolutional Neural Networks for Acoustic Anomaly Detection in Industrial Wood Planers
A Deschênes, R Georges, C Subakan… - arxiv preprint arxiv …, 2025 - arxiv.org
In recent years, the wood product industry has been facing a skilled labor shortage. The
result is more frequent sudden failures, resulting in additional costs for these companies …
result is more frequent sudden failures, resulting in additional costs for these companies …
Improvements of Discriminative Feature Space Training for Anomalous Sound Detection in Unlabeled Conditions
T Fujimura, I Kuroyanagi, T Toda - arxiv preprint arxiv:2409.09332, 2024 - arxiv.org
In anomalous sound detection, the discriminative method has demonstrated superior
performance. This approach constructs a discriminative feature space through the …
performance. This approach constructs a discriminative feature space through the …
[PDF][PDF] Thuee system for first-shot unsupervised anomalous sound detection
This report presents our work for DCASE 2024 Task 2: first shot unsupervised anomalous
sound detection for machine condition monitoring. This year's challenge is heightened by …
sound detection for machine condition monitoring. This year's challenge is heightened by …
[PDF][PDF] THE NU SYSTEMS FOR DCASE 2024 CHALLENGE TASK 2
T Fujimura, I Kuroyanagi, T Toda - Structure, 2024 - dcase.community
In this report, we present our developed anomalous sound detection (ASD) systems for
DCASE 2024 Challenge Task 2. We propose three methods to improve ASD systems based …
DCASE 2024 Challenge Task 2. We propose three methods to improve ASD systems based …
Representational learning for an anomalous sound detection system with source separation model
S Shin, S Lee - arxiv preprint arxiv:2410.21797, 2024 - arxiv.org
The detection of anomalous sounds in machinery operation presents a significant challenge
due to the difficulty in generalizing anomalous acoustic patterns. This task is typically …
due to the difficulty in generalizing anomalous acoustic patterns. This task is typically …
Self-Supervised Augmented Diffusion Model for Anomalous Sound Detection
J Yin, W Zhang, M Zhang, Y Gao - 2024 Asia Pacific Signal and …, 2024 - ieeexplore.ieee.org
Generative models have significantly enhanced the capability of unsupervised anomalous
sound detection (ASD) with their strong data modeling capabilities. However, many existing …
sound detection (ASD) with their strong data modeling capabilities. However, many existing …
Annotation-free Fine-tuning for Unsupervised Anomalous Sound Detection
K Guo, X **e, F Zhang - 2024 Asia Pacific Signal and …, 2024 - ieeexplore.ieee.org
The goal of unsupervised anomalous sound detection (ASD) for industrial machines is to
identify anomalous sounds using only normal sounds for training. A common method is to …
identify anomalous sounds using only normal sounds for training. A common method is to …
[PDF][PDF] Enhanced unsupervised anomalous sound detection using conditional autoencoder for machine condition monitoring
R Zhao, K Ren, L Zou - 2024 - dcase.community
This report outlines our approach to first-shot unsupervised anomalous sound detection for
machine condition monitoring, developed for the DCASE 2024 Challenge Task 2. Given the …
machine condition monitoring, developed for the DCASE 2024 Challenge Task 2. Given the …
[PDF][PDF] Unified Anomaly Detection for Machine Condition Monitoring: Handling Attribute-Rich and Attribute-Free Scenarios
F Chu, Y Zhou, M Qian - 2024 - dcase.community
In this report, we present our solution to the DCASE 2024 Challenge Task 2, focusing on
First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring …
First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring …