AaSP learns aliasing-stable audio representations by augmenting patch tokens with adaptive subband features from alias-prone bands and using teacher-student masked modeling plus multi-mask contrastive regularization, reaching SOTA on AS-20K, ESC-50, and NSynth under fine-tuning.
ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Rep- resentation Learning
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AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers
AaSP learns aliasing-stable audio representations by augmenting patch tokens with adaptive subband features from alias-prone bands and using teacher-student masked modeling plus multi-mask contrastive regularization, reaching SOTA on AS-20K, ESC-50, and NSynth under fine-tuning.