10 citations · 10 across the 8 of their papers we have counts for
9 papers
Towards Event-Robust Acoustic Scene Classification
Yiqiang Cai, Bohan Hu, Yu Yang +3
This paper introduces the Event-Shifted Acoustic Scene (ESAS) dataset, a novel benchmark for evaluating the robustness of Acoustic Scene Classification (ASC) systems against unknow…
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…
Leveraging Self-supervised Audio Representations for Data-Efficient Acoustic Scene Classification
Yiqiang Cai, Shengchen Li, Xi Shao
Acoustic scene classification (ASC) predominantly relies on supervised approaches. However, acquiring labeled data for training ASC models is often costly and time-consuming. Recen…
TF-SepNet: An Efficient 1D Kernel Design in CNNs for Low-Complexity Acoustic Scene Classification
Yiqiang Cai, Peihong Zhang, Shengchen Li
Recent studies focus on developing efficient systems for acoustic scene classification (ASC) using convolutional neural networks (CNNs), which typically consist of consecutive kern…
Exploring the Effects of Channel Sparsity on Neural Network Pruning for Acoustic Scene Classification
Yiqiang Cai, Shengchen Li
Acoustic Scene Classification (ASC) algorithms are usually expected to be deployed in resource-constrained systems. Existing works reduce the complexity of ASC algorithms by prunin…