About this Item
- FMA : a dataset for music analysis.
- Other Title
- Free music archive
- Contributor Names
- WFMU (Radio station : Montclair, N.J.)
- Created / Published
- Subject Headings
- - Musical analysis
- Sound recordings
- - The full dataset includes over 100,000 ful length MP3 audio recordings, and truncated files. There are four .csv metadata files that include: track-level information (such as ID, title, artist, genres, tags and play counts), genre IDs, data generated using LibRosa (a package for music and audio analysis), and data generated by echonest (applicable to a subset of the records). A published paper is a single PDF document, and code (notebooks and scripts) that have been developed for interacting with the dataset and metadata files. The Library is currently only able to provide dowload access for the smallest version of the dataset. Visit the GitHub archive in order to download the larger versions.
- - Description based on GitHub page, Sept. 25, 2018.
- s-Online Electronic Resource
- Digital Id
- https://github.com/mdeff/fma External
- Library of Congress Control Number
- Rights Advisory
- The majority of the audio in the FMA is licensed as either Creative Commons or Public Domain, while a smaller portion are under less common licenses. The code is available under the MIT license, and the paper and metadata files are released under the CC BY 4.0 license.
- Online Format
- compressed data
- LCCN Permalink
- Additional Metadata Formats
- MARCXML Record
- MODS Record
- Dublin Core Record
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More about Copyright and other Restrictions
Credit Line: Library of Congress, Digital Collections Management and Services Division
Citations are generated automatically from bibliographic data as a convenience, and may not be complete or accurate.
Chicago citation style:
Wfmu. FMA: a dataset for music analysis. 2017. Software, E-Resource. https://www.loc.gov/item/2018655052/.
APA citation style:
Wfmu. (2017) FMA: a dataset for music analysis. [Software, E-Resource] Retrieved from the Library of Congress, https://www.loc.gov/item/2018655052/.
MLA citation style:
Wfmu. FMA: a dataset for music analysis. 2017. Software, E-Resource. Retrieved from the Library of Congress, <www.loc.gov/item/2018655052/>.
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