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Publised on June 8, 2024

COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio
Representations

COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio
Representations

Dive into the fascinating world of musical audio representations with
COCOLA (Coherence-Oriented Contrastive Learning for Audio), a novel
contrastive learning method that captures harmonic and rhythmic
coherence in music tracks. Discover how COCOLA evaluates
compositional models for accompaniment generation and introduces
CompoNet, a new baseline for compositional music generation based on
ControlNet. Explore the potential of COCOLA in training models on
public datasets like MUSDB18-HQ, MoisesDB, Slakh2100, and
CocoChorales.

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