Quantitative evaluation of music quality in symbolic generation

Determine reliable quantitative evaluation methodologies for music quality in symbolic music generation that can be used for objective assessment and comparison of generated music across models and datasets.

Background

In their experimental evaluation, the authors need objective measures to compare the quality of music produced by different generative models and configurations. They note that, despite various proxy metrics, establishing a robust quantitative evaluation framework for music quality remains unresolved.

As a practical workaround, the paper employs overlapping area (OA) metrics across several musical attributes as a necessary condition for good quality, and supplements this with listening tests. However, the authors explicitly state that quantitative evaluation of music quality is still an open problem, underscoring the need for more principled, validated metrics.