The rise of Artificial Intelligence (AI) in music offers creative potential but also raises complex challenges, especially in assessing originality and possible copyright infringement by generative models.
The Music Replication Assessment (MiRA) tool was designed to identify potential data replication using audio-based similarity metrics. However, its alignment with human perception and legal standards has not been demonstrated. To explore this, we conducted a perceptual experiment comparing human judgments, MiRA classifications, and legal rulings on melodic similarity. Participants completed two tasks: (1) rating similarity on a scale, and (2) a forced choice to judge whether a fragment was a copy. Results revealed discrepancies among the three perspectives. Legal rulings aligned more with the forced choice task, while MiRA matched direct scaling, particularly in ambiguous cases.
