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Abstract:
MELONET I is a multi-scale neural network system producing
baroque-style melodic variations. Given a melody, the system
invents a four-part chorale harmonization and a variation of any
chorale voice, after being trained on music pieces of composers
like J. S. Bach and J. Pachelbel. Unlike earlier approaches to the
learning of melodic structure, the system is able to learn and
reproduce high-order structure like harmonic, motif and phrase
structure in melodic sequences. This is achieved by using mutually
interacting feedforward networks operating at different time
scales, in combination with Kohonen networks to classify and
recognize musical structure. The results are chorale partitas in
the style of J. Pachelbel. Their quality has been judged by experts
to be comparable to improvisations invented by an experienced human
organist.
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