A Genetic Musician Thematic Music Generation with Genetic Algorithms

Outline Introduction Song Structure First Genetic Algorithm : The Root Melody Second Genetic Algorithm : The Harmonizing Voices Results and Conclusion Questions

Introduction Very Little Practical Value? – Human Curiosity Implementation employs two separate GAs to create songs with Variations of common themes User sets parameters via parameter files – GA parameters for both genetic algorithms – Song structure

Song Structure ACBABBABCC Root A Harm A

Root Melody: Genomes Two separate sets of Genomes – The notes 12 Semitones – A, A#/Bb, B, C, C#/Db, D, D#/Eb, E, F, F#/Gb, G, G#/Ab Rest Hold – The Octaves 4 octave range 1 null octave (rest, hold) Size of individual is dependent upon notelength and time signature – 8 eighth-notes per measure = 16 total genomes

Root Melody: Note Shorten and Note Extend Operators Note Shorten – Shortens the length of a note or rest Note Extend – Extends the length of a note or rest Shorten Operator OD rstChd1020 NDrstCB1021 Extend Operator OA#hdCF#1023 NA#hd F#1003

Root Melody: Note Change and Octave Change Note Change – Changes a note or rest Octave Change – Changes the octave of a note Note Change Operator OD rstCG1021 ND CB1021 Octave Change Operator OA#hdCF#1023 NA#hdCF#1033

Root Melody: Fitness Function Multi-Objective Fitness Function – Key – Octave – Note Percentage

Transition Once the measures are sufficiently-evolved, a string of measures from the same population is used to create the root melody This root melody is used for every movement of the same theme

Harmonizing Voices: Genomes and Operators Genomes and Operators same as in First Genetic Algorithm Individuals hold information for full movement, instead of just single measures

Harmonizing Voices: Fitness Function Consonance Matrix Chords – Minor chords – Major chords Octave Key Note Percentage

Results Results Chaotic with Moments of Clarity Parameters are hard to analyze Midi 1 Midi 2 Midi 3 Midi 4 Midi 5 Midi 6

fin Questions?