Computer Aided Composition Kevin Wampler. Assisted Notation and Layout Automated Composition Style-driven Suggestions Alternative Notations Automatic.

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Presentation transcript:

Computer Aided Composition Kevin Wampler

Assisted Notation and Layout Automated Composition Style-driven Suggestions Alternative Notations Automatic Harmonization Musical Scripting more automation less automation

Computer Aided Composition Automatic Composition

Computer Aided Composition Automatic Composition

Alternative Notations

UPIC

time pitch

Mycenae Alpha (excerpt)

Hyperscore

motif Harmonization line tension resolution Key changes

Musical Programming

Patchwork

Graphical LISP Framework

Libraries Spectral music Stochastic and dynamic models Constraint-based music generation Rhythmic tools Etc.

Constraint Satisfaction Common technique User specifies: –Search space –Constraints –Heuristics System searches for a solution, generally: –Constraint propagation (or forward checking) –Backtracking (or backjumping)

Automatic Harmonization

CHORAL Harmonizes a chorale in the style of Bach Expert system by Ebcioglu et. al Written in BSL Predicate logic on multiple views Solved with a backtracking algorithm Very complex “bordering on intractable”

Views Chord skeleton Fill-in Time slice Melodic string Merged melodic string Schenkerian analysis

Tonica Neural network chorale harmonization User specifies: –Chorale melody –Harmonization style Harmonization in three steps: –Determine chords –Realize chords –Add passing notes

Style-based Composition

EMI Expert system by David Cope Mostly automatic, but can give suggestions Music as language –Parse set of scores –Identify similarities –Recombine according to grammar

Signature Detection

ATN

Recombination

Style-specific Suggestions