3 papers
eess.AS2026
From Objectives to Applications: Aligning Architectural Biases in Audio Self-Supervised Learning
Kele Xu, Yulu Fang, Boda Zhou +6
This paper examines audio self-supervised learning (SSL) through the alignment between pretraining objectives, architectural inductive biases, and downstream applications. Rather t…
cs.SD2025
AudioSet-R: A Refined AudioSet with Multi-Stage LLM Label Reannotation
Yulin Sun, Qisheng Xu, Yi Su +4
AudioSet is a widely used benchmark in the audio research community and has significantly advanced various audio-related tasks. However, persistent issues with label accuracy and c…
cs.SD2024
AudioCIL: A Python Toolbox for Audio Class-Incremental Learning with Multiple Scenes
Qisheng Xu, Yulin Sun, Yi Su +7
Deep learning, with its robust aotomatic feature extraction capabilities, has demonstrated significant success in audio signal processing. Typically, these methods rely on static,…