CloserMusicDB: A Modern Multipurpose Dataset of High Quality Music
This provides a new dataset for music information retrieval researchers, but it is incremental as it focuses on data collection rather than novel methods.
The authors introduced CloserMusicDB, a dataset of high-quality music tracks with expert annotations, and conducted baseline experiments to establish benchmarks for tasks like hook detection, contextual tagging, and artist identification.
In this paper, we introduce CloserMusicDB, a collection of full length studio quality tracks annotated by a team of human experts. We describe the selected qualities of our dataset, along with three example tasks possible to perform using this dataset: hook detection, contextual tagging and artist identification. We conduct baseline experiments and provide initial benchmarks for these tasks.