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We introduce a method for imposing higher-level structure on generated,polyphonic music. A Convolutional Restricted Boltzmann Machine (C-RBM) as agenerative model is combined with gradient descent constraint optimisation toprovide further control over the generation process. Among other things, thisallows for the use of a "template" piece, from which some structural propertiescan be extracted, and transferred as constraints to the newly generatedmaterial. The sampling process is guided with Simulated Annealing to avoidlocal optima, and to find solutions that both satisfy the constraints, and arerelatively stable with respect to the C-RBM. Results show that with thisapproach it is possible to control the higher-level self-similarity structure,the meter, and the tonal properties of the resulting musical piece, whilepreserving its local musical coherence.

Imposing higher-level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints