{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fma-a-dataset-for-music-analysis","title":"FMA: A Dataset For Music Analysis","arxiv_id":"1612.01840","date":"2016-12-06","proceeding":"ISMIR 2017 4","authors":["Michaël Defferrard","Kirell Benzi","Pierre Vandergheynst","Xavier Bresson"],"abstract":"We introduce the Free Music Archive (FMA), an open and easily accessible\ndataset suitable for evaluating several tasks in MIR, a field concerned with\nbrowsing, searching, and organizing large music collections. The community's\ngrowing interest in feature and end-to-end learning is however restrained by\nthe limited availability of large audio datasets. The FMA aims to overcome this\nhurdle by providing 917 GiB and 343 days of Creative Commons-licensed audio\nfrom 106,574 tracks from 16,341 artists and 14,854 albums, arranged in a\nhierarchical taxonomy of 161 genres. It provides full-length and high-quality\naudio, pre-computed features, together with track- and user-level metadata,\ntags, and free-form text such as biographies. We here describe the dataset and\nhow it was created, propose a train/validation/test split and three subsets,\ndiscuss some suitable MIR tasks, and evaluate some baselines for genre\nrecognition. Code, data, and usage examples are available at\nhttps://github.com/mdeff/fma","url_abs":"http://arxiv.org/abs/1612.01840v3","url_pdf":"http://arxiv.org/pdf/1612.01840v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/mdeff/fma","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/Golem8/Music-Genre-Classifier","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/KrishnaManmayi/Music-Data-Visualization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/Manmayi/Music-Data-Visualization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/MorenoLaQuatra/ARCH","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/StatisticDean/Crystal_Clear","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/bhavnasud/MusicRecognition","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/cocktail-fork/cocktail-fork.github.io","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/crowdAI/crowdai-musical-genre-recognition-starter-kit","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/darius522/dnr-utils","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/dcase2024-task7-sound-scene-synthesis/fadtk","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/karn1986/fma_pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/kikwon/fma_project","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/markcutajar/raw-music-tagging-cnns","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/mdeff/paper-fma-ismir2017","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"CC-BY-4.0"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/microsoft/fadtk","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/ucsd-dsc-arts/dsc160-midterm-group2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"fma-a-dataset-for-music-analysis","repo_url":"https://github.com/weepingwillowben/sound-eval","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[{"slug":"fma","name":"FMA","full_name":"Free Music Archive"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1612.01840","atlas_url":"https://app.syntology.ai/?focus=1612.01840","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1612.01840"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; 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