Towards Automated Quality Assessment Methods in Algorithmic Music Composition

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Csaba:2019:SYNASC,

• author = "Sulyok Csaba",
• title = "Towards Automated Quality Assessment Methods in Algorithmic Music Composition",
• booktitle = "2019 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)",
• year = "2019",
• pages = "155--158",
• month = "4-7 " # sep,
• address = "Timisoara, Romania",
• keywords = "genetic algorithms, genetic programming, fitness raters, linear genetic programming, evolutionary algorithms, algorithmic music composition, MIDI",
• isbn13 = "978-1-7281-5725-2",
• DOI = "doi:10.1109/SYNASC49474.2019.00029",
• size = "4 pages",
• abstract = "The current work in progress paper describes a proof of concept for an automatic fitness evaluator in an evolutionary music composition setting. The associated research project proposes a novel algorithmic music creation mechanism. It uses linear genetic programming to create short musical pieces statistically similar to real-world pieces from a corpus. We present two fully automatic quality assessment methods for music, both used as fitness functions in the genetic algorithm: one proposed in a previous research stage, as well as a novel one involving n-grams. Experiments are proposed and described for comparing these measurement mechanisms to each other as well as to other automated methods present in the literature.",
• notes = "Also known as \cite{9049871}",

}

Genetic Programming entries for Csaba Sulyok

Citations