From the 1 of 7 linked papers with an AI index.
7 papers
Towards Event-Robust Acoustic Scene Classification
Yiqiang Cai, Bohan Hu, Yu Yang +3
The paper presents the Event-Shifted Acoustic Scene (ESAS) dataset, a benchmark that adds foreground sound events to background scenes to test how well acoustic scene classificatio…
Remix the Timbre: Diffusion-Based Style Transfer Across Polyphonic Stems
Leduo Chen, Junchuan Zhao, Shengchen Li
Timbre transfer aims to modify the timbral identity of a musical recording while preserving the original melody and rhythm. While single-instrument timbre transfer has made substan…
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…
Training a Perceptual Model for Evaluating Auditory Similarity in Music Adversarial Attack
Yuxuan Liu, Rui Sang, Peihong Zhang +2
Music Information Retrieval (MIR) systems are highly vulnerable to adversarial attacks that are often imperceptible to humans, primarily due to a misalignment between model feature…