Data of research project: About the impact of audio quality and codecs on genre classification and BPM recognition in Essentia

doi:10.4121/18737156.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/18737156
Datacite citation style:
Sjoerd Hulleman (2022): Data of research project: About the impact of audio quality and codecs on genre classification and BPM recognition in Essentia. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/18737156.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
A dataset of songs used in the Research Project of Q2 2021-2022 at the TU Delft. Research paper was about the impact of audio quality and codecs on genre classification and BPM recognition in Essentia. This dataset has been compiled for data collection from Muziekweb. Muziekweb could provide our research group with music in high quality FLAC format. This was essential to this research, since we were researching the impact of audio quality. FLAC is one of the highest quality (lossless) audio codecs.
history
  • 2022-01-24 first online, published, posted
publisher
4TU.ResearchData
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science

DATA

files (2)