CloserMusicDB: A Modern Multipurpose Dataset of High Quality Music
Sound
2024-10-28 v1 Artificial Intelligence
Machine Learning
Audio and Speech Processing
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.
Keywords
Cite
@article{arxiv.2410.19540,
title = {CloserMusicDB: A Modern Multipurpose Dataset of High Quality Music},
author = {Aleksandra Piekarzewicz and Tomasz Sroka and Aleksander Tym and Mateusz Modrzejewski},
journal= {arXiv preprint arXiv:2410.19540},
year = {2024}
}