Survey on the Evaluation of Generative Models in Music
This is a survey paper that synthesizes existing knowledge for researchers in music, AI, and HCI, making it incremental in nature.
The paper reviews evaluation methods for generative music systems, examining targets, methodologies, and metrics from interdisciplinary perspectives, but does not report specific results or numbers.
Research on generative systems in music has seen considerable attention and growth in recent years. A variety of attempts have been made to systematically evaluate such systems. We present an interdisciplinary review of the common evaluation targets, methodologies, and metrics for the evaluation of both system output and model use, covering subjective and objective approaches, qualitative and quantitative approaches, as well as empirical and computational methods. We examine the benefits and limitations of these approaches from a musicological, an engineering, and an HCI perspective.