Name
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/iV.2017.49 | 2017 21st International Conference Information Visualisation (IV) |
Keywords | DocType | ISBN |
Information Visualization,Graph Visualization,Music Plagiarism,Melodic Similarity,User Evaluation | Conference | 978-1-5386-0832-6 |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto De Prisco | 1 | 574 | 55.43 |
| Antonio Esposito | 2 | 78 | 18.72 |
| Nicola Lettieri | 3 | 7 | 1.91 |
| Delfina Malandrino | 4 | 310 | 44.08 |
| Donato Pirozzi | 5 | 43 | 9.28 |
| Gianluca Zaccagnino | 6 | 27 | 5.55 |
| Rocco Zaccagnino | 7 | 64 | 17.27 |