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COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio Representations
April 29, 2024, 4:42 a.m. | Ruben Ciranni, Emilian Postolache, Giorgio Mariani, Michele Mancusi, Luca Cosmo, Emanuele Rodol\`a
cs.LG updates on arXiv.org arxiv.org
Abstract: We present COCOLA (Coherence-Oriented Contrastive Learning for Audio), a contrastive learning method for musical audio representations that captures the harmonic and rhythmic coherence between samples. Our method operates at the level of stems (or their combinations) composing music tracks and allows the objective evaluation of compositional models for music in the task of accompaniment generation. We also introduce a new baseline for compositional music generation called CompoNet, based on ControlNet \cite{zhang2023adding}, generalizing the tasks of …
abstract arxiv audio cs.lg cs.sd eess.as evaluation music samples type
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