Measuring When a Music Generation Algorithm Copies Too Much: The Originality Report, Cardinality Score, and Symbolic Fingerprinting by Geometric Hashing

Journal article

Peer reviewed

Zongyu Yin, Federico Reuben, Susan Stepney and Tom Collins

SN computer science, Vol.3(5), p.340

2022-09-01

Abstract

Deep learning

Markov model

Music generation

Originality evaluation

url

https://doi.org/10.1007/s42979-022-01220-yView

Published (Version of record) Open

1 Record Views

Title: Measuring When a Music Generation Algorithm Copies Too Much: The Originality Report, Cardinality Score, and Symbolic Fingerprinting by Geometric Hashing
Creators: Zongyu Yin - University of York
Federico Reuben - University of York
Susan Stepney - University of York
Tom Collins - University of York
Publication Details: SN computer science, Vol.3(5), p.340
Academic Unit: Frost School of Music; Frost School of Music - Music Engineering; MUSIC ENGINEERING Department
Language: English
Resource Type: Journal article
Record Identifier: 991032796056202976