Audio Barlow Twins: Self-Supervised Audio Representation Learning. (arXiv:2209.14345v1 [cs.SD])

The Barlow Twins self-supervised learning objective requires neither negative
samples or asymmetric learning updates, achieving results on a par with the
current state-of-the-art within Computer Vision. As such, we present Audio
Barlow Twins, a novel self-supervised audio representation learning approach,
adapting Barlow Twins to the audio domain. We pre-train on the large-scale
audio dataset AudioSet, and evaluate the quality of the learnt representations
on 18 tasks from the HEAR 2021 Challenge, achieving results which outperform,
or otherwise are on a par with, the current state-of-the-art for instance
discrimination self-supervised learning approaches to audio representation
learning. Code at



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