Evaluating Deep Music Generation Methods Using Data Augmentation
Evaluating Deep Music Generation Methods Using Data Augmentation
Despite advances in deep algorithmic music generation, evaluation of generated samples often relies on human evaluation, which is subjective and costly. We focus on designing a homogeneous, objective framework for evaluating samples of algorithmically generated music. Any engineered measures to evaluate generated music typically attempt to define the samples' musicality, …