We introduce a method for imposing higher-level structure on generated, polyphonic music. A Convolutional Restricted Boltzmann Machine (C-RBM) as a generative model is combined with gradient descent constraint optimization to provide further control over the generation process. Among other things, this allows for the use of a "template" piece, from which some structural properties can be extracted, and transferred as constraints to newly generated material. The sampling process is guided with Simulated Annealing in order to avoid local optima, and find solutions that both satisfy the constraints, and are relatively stable with respect to the C-RBM. Results show that with this approach it is possible to control the higher level self-similarity structure, the meter, as well as tonal properties of the resulting musical piece while preserving its local musical coherence.

通过结合卷积限制玻尔兹曼机、梯度下降约束优化和模拟退火，我们引入了一种在生成的多声部音乐中强制施加更高层次结构的方法，证明了该方法可以控制生成乐曲的更高层次自相似结构、音高属性和保持其局部音乐连贯性。

使用卷积受限玻尔兹曼机和约束条件在多声部音乐生成中施加高层次结构