Music Plagiarism at a Glance: Metrics of Similarity and Visualizations

R. Prisco, A. Esposito, N. Lettieri, Delfina Malandrino, Donato Pirozzi, Gianluca Zaccagnino, R. Zaccagnino
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引用次数: 20

Abstract

The plagiarism is a debated topic in different fields and in particular in music, given the huge amount of money that music is able to generate. Moreover, it is controversial aspect in the law's field given the subjectivity of the judges that have to pronounce on a suspicious case. Automatic detection of music plagiarism is fundamental to overcome these limits by representing an useful support for judges during their pronouncements and an important result to avoid musicians to spend more time in court than on composing and playing music.In this paper we address this issue by defining a new metric to discover pop music similarity and we study whether visualization can assist domain experts in judging suspicious cases. We describe a user study in which subjects performed different tasks on a song collection using different visual representations to investigate which one is best in terms of intuitiveness and accuracy. Results provided us with positive feedback about our choices and some useful suggestions for future directions.
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音乐剽窃一览:相似性和可视化的度量
剽窃在不同的领域都是一个有争议的话题,特别是在音乐领域,因为音乐能够产生大量的钱。此外,由于法官必须对可疑案件作出判决的主观性,这在法律界也是一个有争议的方面。音乐剽窃的自动检测是克服这些限制的基础,它为法官在判决过程中提供了有用的支持,也是避免音乐家在法庭上花费比作曲和演奏更多的时间的重要结果。在本文中,我们通过定义一个新的度量来发现流行音乐相似度来解决这个问题,并研究可视化是否可以帮助领域专家判断可疑案件。我们描述了一项用户研究,其中受试者使用不同的视觉表示对歌曲集合执行不同的任务,以调查哪一个在直观性和准确性方面是最好的。结果为我们的选择提供了积极的反馈,并为未来的发展方向提供了一些有用的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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