SOURCE-LINKED INTELLIGENCE
On the Human and Computer Alignment of Attribute-Based Music Matches
Recent advances in generative AI are raising ethical concerns regarding the originality of generated content and the potential replication of training data, with further implications for transparency, attribution, and intellectual property. In music, several computational approaches have been proposed to identify potential replication, using audio-based similarity metrics. Yet, their alignment with human judgments across distinct musical attributes remains underexplored. To address this gap, we conduct a perceptual experiment on music matches, defined as strongly similar musical excerpts. We f
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- arXiv · AI, language, vision and robotics · 2026-09-01T09:41:29.000Z
First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.