10 citations · 14 across the 7 of their papers we have counts for
7 papers
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…
FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation
Pingyi Fan, Anbai Jiang, Shuwei Zhang +9
Industrial signal analysis is hindered by severe data heterogeneity, which we characterize as the M5 problem. Existing solutions rely on specialized models that lack robustness and…
Generalizable Audio Deepfake Detection via Latent Space Refinement and Augmentation
Wen Huang, Yanmei Gu, Zhiming Wang +2
Advances in speech synthesis technologies, like text-to-speech (TTS) and voice conversion (VC), have made detecting deepfake speech increasingly challenging. Spoofing countermeasur…
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…
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…
GSTalker: Real-time Audio-Driven Talking Face Generation via Deformable Gaussian Splatting
Bo Chen, Shoukang Hu, Qi Chen +4
We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 35 m…