5 papers · 1 filter
Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection
Bing Han, Anbai Jiang, Xinhu Zheng +4
Machine anomalous sound detection (ASD) is a valuable technique across various applications. However, its generalization performance is often limited due to challenges in data coll…
Data-Efficient Low-Complexity Acoustic Scene Classification via Distilling and Progressive Pruning
Bing Han, Wen Huang, Zhengyang Chen +7
The goal of the acoustic scene classification (ASC) task is to classify recordings into one of the predefined acoustic scene classes. However, in real-world scenarios, ASC systems…
Improving Anomalous Sound Detection via Low-Rank Adaptation Fine-Tuning of Pre-Trained Audio Models
Xinhu Zheng, Anbai Jiang, Bing Han +4
Anomalous Sound Detection (ASD) has gained significant interest through the application of various Artificial Intelligence (AI) technologies in industrial settings. Though possessi…
CoopASD: Cooperative Machine Anomalous Sound Detection with Privacy Concerns
Anbai Jiang, Yuchen Shi, Pingyi Fan +2
Machine anomalous sound detection (ASD) has emerged as one of the most promising applications in the Industrial Internet of Things (IIoT) due to its unprecedented efficacy in mitig…
AnoPatch: Towards Better Consistency in Machine Anomalous Sound Detection
Anbai Jiang, Bing Han, Zhiqiang Lv +6
Large pre-trained models have demonstrated dominant performances in multiple areas, where the consistency between pre-training and fine-tuning is the key to success. However, few w…