Understanding Human Perception of Music Plagiarism Through a Computational Approach
Abstract
There is a wide variety of music similarity detection algorithms, while discussions about music plagiarism in the real world are often based on audience perceptions. Therefore, we aim to conduct a study to examine the key criteria of human perception of music plagiarism, focusing on the three commonly used musical features in similarity analysis: melody, rhythm, and chord progression. After identifying the key features and levels of variation humans use in perceiving musical similarity, we propose a LLM-as-a-judge framework that applies a systematic, step-by-step approach, drawing on modules that extract such high-level attributes.
Cite
@article{arxiv.2601.02586,
title = {Understanding Human Perception of Music Plagiarism Through a Computational Approach},
author = {Daeun Hwang and Hyeonbin Hwang},
journal= {arXiv preprint arXiv:2601.02586},
year = {2026}
}
Comments
3 pages, D. Hwang and H. Hwang, Understanding Human Perception of Music Plagiarism Through a Computational Approach, in Extended Abstracts for the Late-Breaking Demo Session of the 25th Int. Society for Music Information Retrieval Conf., San Francisco, United States, 2024