CloserMusicDB: A Modern Multipurpose Dataset of High Quality Music

TL;DR

CloserMusicDB is a high-quality, annotated music dataset designed for multiple music analysis tasks, providing a foundation for research in hook detection, tagging, and artist identification.

Contribution

This paper introduces CloserMusicDB, a comprehensive, studio-quality music dataset with expert annotations, enabling new research in music analysis tasks.

Findings

Baseline experiments established initial benchmarks.

Dataset covers hook detection, tagging, and artist ID.

High-quality annotations support diverse research.

Abstract

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.