Examining melodic similarity across human, computational, and legal perspectives

Abstract

Comunicació presentada al 3rd Workshop on Human-Centric Music Information Research (HCMIR25), celebrada a Daejeon (Korea) el 20 de setembre de 2025.

As music-generative AI continues to evolve, critical concerns are emerging around originality, data replication, and the misuse of intellectual property. The Music Replication Assessment (MiRA) tool was proposed to detect potential data replication using audio-based similarity metrics. However, it remains unclear how its classifications align with human perception or legal judgments. Thus, this study aims to examine melodic similarity across human, computational, and legal perspectives. We conducted a perceptual experiment based on real-world copyright infringement cases, where participants completed two tasks: (1) a direct rating of melodic similarity, and (2) a forced-choice judgment on potential copying. Participants’ responses were compared with MiRA’s similarity scores and court rulings. Results revealed systematic discrepancies: legal decisions tended to align with forced-choice judgments, while MiRA corresponded more closely with rating patterns, particularly in ambiguous cases. These findings highlight the complexity of assessing music similarity and emphasise the need to incorporate human-centred evaluation into computational tools and legal discourse around AI-generated music.