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cs.SD2024
Discogs-VI: A Musical Version Identification Dataset Based on Public Editorial Metadata
R. Oguz Araz, Xavier Serra, Dmitry Bogdanov
Current version identification (VI) datasets often lack sufficient size and musical diversity to train robust neural networks (NNs). Additionally, their non-representative clique s…
cs.SD2024
Leveraging Pre-Trained Autoencoders for Interpretable Prototype Learning of Music Audio
Pablo Alonso-Jiménez, Leonardo Pepino, Roser Batlle-Roca +4
We present PECMAE, an interpretable model for music audio classification based on prototype learning. Our model is based on a previous method, APNet, which jointly learns an autoen…