Generation of Pop-Rock Chord Sequences Using Genetic Algorithms and Variable Neighborhood Search

Authors:
Leonardo Lozano;Andrés L. Medaglia;Nubia Velasco
Affiliations:
Departamento de Ingeniería Industrial Centro de Optimización y Probabilidad Aplicada, Universidad de los Andes,;Departamento de Ingeniería Industrial Centro de Optimización y Probabilidad Aplicada, Universidad de los Andes,;Departamento de Ingeniería Industrial Centro de Optimización y Probabilidad Aplicada, Universidad de los Andes,
Venue:
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Year:
2009

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Abstract

This work proposes a utility function that measures: 1) the vertical relation between notes in a melody and chords in a sequence, and 2) the horizontal relation among chords. This utility function is embedded in a procedure that combines a Genetic Algorithm (GA) with a Variable Neighborhood Search (VNS) to automatically generate style-based chord sequences. The two-step algorithm is tested in ten popular songs, achieving accompaniments that match closely those of the original versions.