RT Journal Article
T1 Using Formal Grammars as Musical Genome
A1 Albarracin-Molina, David D.
A1 Raglio, Alfredo
A1 Rivas-Ruiz, Francisco
A1 Vico, Francisco J.
K1 generative music
K1 formal grammars
K1 L-systems
K1 evolutionary computation
K1 genetic algorithms
K1 music perception
K1 Human emotions
K1 Turing test
K1 Models
K1 Creativity
AB In this paper, we explore a generative music method that can compose atonal and tonal music in different styles. One of the main differences between regular engineering problems and artistic expressions is that goals and constraints are usually ill-defined in the latter case; in fact the rules here could or should be transgressed more regularly. For this reason, our approach does not use a pre-existing dataset to imitate or extract rules from. Instead, it uses formal grammars as a representation method than can retain just the basic features, common to any form of music (e.g., the appearance of rhythmic patterns, the evolution of tone or dynamics during the composition, etc.). Exploring different musical spaces is the responsibility of a program interface that translates musical specifications into the fitness function of a genetic algorithm. This function guides the evolution of those basic features enabling the emergence of novel content. In this study, we then assess the outcome of a particular music specification (guitar ballad) in a controlled real-world setup. As a result, the generated music can be considered similar to human-composed music from a perceptual perspective. This endorses our approach to tackle arts algorithmically, as it is able to produce novel content that complies with human expectations.
PB Mdpi
YR 2021
FD 2021-05-01
LK http://hdl.handle.net/10668/19245
UL http://hdl.handle.net/10668/19245
LA en
DS RISalud
RD Apr 9, 2025