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Found 4 papers, 2 papers with code
On the Effectiveness of Speech Self-supervised Learning for Music
Our findings suggest that training with music data can generally improve performance on MIR tasks, even when models are trained using paradigms designed for speech.
MARBLE: Music Audio Representation Benchmark for Universal Evaluation
This is evident in the limited work on deep music representations, the scarcity of large-scale datasets, and the absence of a universal and community-driven benchmark.
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
Although SSL has been proven effective in speech and audio, its application to music audio has yet to be thoroughly explored.
MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music Audio Representation Learning
The deep learning community has witnessed an exponentially growing interest in self-supervised learning (SSL).
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