Functional Music (I) Amanda Crawford Hons. Comp.Sci Monash University, Australia. Supervisors: Lloyd Allison, Jon McCormack

Overview Background information Musical terms Project aims Design Implementation Results Conclusions Future work Further information Acknowledgements

Background information

Musical terms TempoTime signature Bar

Musical terms (cont…) Key Chord Chord progression Arpeggio

Project aims Analyse MIDI files for time signature(s), tempo, instruments Break the MIDI file into bars Create new music –chord progressions and melody –use guitar chords

Design methods (I) Statistical analysis –extract time signature, calculate bars –calculate running time of file –calculate tempo (beats per min), key, instruments.

Design methods (II) Generating new music –random key –select chords according to programmed harmonic rules –generate melody from arpeggio of each chord

Implementation Functional programming paradigm Haskell Haskore Computer Music System –modules and functions extracting tempo(s), time signature(s) making new music: programming music theory guitar chords

Example of Haskore

Results (I) Analysis –MIDI files on Internet: blues music –artists included: –example: 12 Bar blues Key: E major, Tempo: 85bpm, Length: 76 bars

Example of output

Results (II) Play some sound samples –12 Bar blues in E major –some new music very first file some examples of chord and melody multiple instruments

Conclusions Blues music varies in key, tempo Music theory so new music sounds “pleasant” MIDI files - low sound quality Haskore code hard to learn, initial progress slow Arpeggios – good way of creating harmony over chords

Future work Make the code more efficient Account for more than one time signature (statistical analysis) Improve the generation of new music –coded music theory about key –add more guitar chords

Further information Web:

Acknowledgements My supervisors – Lloyd and Jon Simon McNeilly Fellow Honours students Family Friends Musician friends – Brett, Andrew

The End Questions?