@misc{10481/76953,
year = {2022},
month = {8},
url = {https://hdl.handle.net/10481/76953},
abstract = {We present GenoMus, a new model for artificial musical creativity based on a procedural
approach, able to represent compositional techniques behind a musical score. This model aims to
build a framework for automatic creativity, that is easily adaptable to other domains beyond music.
The core of GenoMus is a functional grammar designed to cover a wide range of styles, integrating
traditional and contemporary composing techniques. In its encoded form, both composing methods
and music scores are represented as one-dimensional arrays of normalized values. On the other
hand, the decoded form of GenoMus grammar is human-readable, allowing for manual editing
and the implementation of user-defined processes. Musical procedures (genotypes) are functional
trees, able to generate musical scores (phenotypes). Each subprocess uses the same generic functional
structure, regardless of the time scale, polyphonic structure, or traditional or algorithmic process
being employed. Some works produced with the algorithm have been already published. This highly
homogeneous and modular approach simplifies metaprogramming and maximizes search space. Its
abstract and compact representation of musical knowledge as pure numeric arrays is optimized for
the application of different machine learning paradigms.},
organization = {FEDER/Junta de Andalucia	A.TIC.244.UGR20
Spanish Government},
organization = {European Commission	PID2021-125537NA-I00},
publisher = {MDPI},
keywords = {Automatic musical composition},
keywords = {Metaprogramming},
keywords = {Procedural representation of music},
keywords = {Artificial creativity},
keywords = {GenoMus},
title = {GenoMus: Representing Procedural Musical Structures with an Encoded Functional Grammar Optimized for Metaprogramming and Machine Learning},
doi = {10.3390/app12168322},
author = {López Montes, José and Molina Solana, Miguel José and Fajardo Contreras, Waldo},
}