6 papers
Membership Inference Attack Against Music Diffusion Models via Generative Manifold Perturbation
Yuxuan Liu, Peihong Zhang, Rui Sang +4
Membership inference attacks (MIAs) test whether a specific audio clip was used to train a model, making them a key tool for auditing generative music models for copyright complian…
TopSeg: A Multi-Scale Topological Framework for Data-Efficient Heart Sound Segmentation
Peihong Zhang, Zhixin Li, Yuxuan Liu +4
Deep learning approaches for heart-sound (PCG) segmentation built on time-frequency features can be accurate but often rely on large expert-labeled datasets, limiting robustness an…
DDSC: Dynamic Dual-Signal Curriculum for Data-Efficient Acoustic Scene Classification under Domain Shift
Peihong Zhang, Yuxuan Liu, Rui Sang +4
Acoustic scene classification (ASC) suffers from device-induced domain shift, especially when labels are limited. Prior work focuses on curriculum-based training schedules that str…
NMCSE: Noise-Robust Multi-Modal Coupling Signal Estimation Method via Optimal Transport for Cardiovascular Disease Detection
Peihong Zhang, Zhixin Li, Rui Sang +4
The coupling signal refers to a latent physiological signal that characterizes the transformation from cardiac electrical excitation, captured by the electrocardiogram (ECG), to me…
Improving Acoustic Scene Classification with City Features
Yiqiang Cai, Yizhou Tan, Shengchen Li +2
Acoustic scene recordings are often collected from a diverse range of cities. Most existing acoustic scene classification (ASC) approaches focus on identifying common acoustic scen…
Exploring Differences between Human Perception and Model Inference in Audio Event Recognition
Yizhou Tan, Yanru Wu, Yuanbo Hou +5
Audio Event Recognition (AER) traditionally focuses on detecting and identifying audio events. Most existing AER models tend to detect all potential events without considering thei…