Automatic generation of chord progressions with an artificial immune system
Tipo
Artigo de evento
Data de publicação
2015
Periódico
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Citações (Scopus)
22
Autores
Navarro M.
Caetano M.
Bernardes G.
de Castro L.N.
Corchado J.M.
Caetano M.
Bernardes G.
de Castro L.N.
Corchado J.M.
Orientador
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
© Springer International Publishing Switzerland 2015.Chord progressions are widely used in music. The automatic generation of chord progressions can be challenging because it depends on many factors, such as the musical context, personal preference, and aesthetic choices. In this work, we propose a penalty function that encodes musical rules to automatically generate chord progressions. Then we use an artificial immune system (AIS) to minimize the penalty function when proposing candidates for the next chord in a sequence. The AIS is capable of finding multiple optima in parallel, resulting in several different chords as appropriate candidates. We performed a listening test to evaluate the chords subjectively and validate the penalty function. We found that chords with a low penalty value were considered better candidates than chords with higher penalty values.
Descrição
Palavras-chave
Assuntos Scopus
Artificial Immune System , Automatic Generation , Chord progressions , Consonance , Harmony , Listening tests , Penalty function , Personal preferences