{"url":"/dataset/musicnet","name":"MusicNet","full_name":null,"description_markdown":"MusicNet is a collection of 330 freely-licensed classical music recordings, together with over 1 million annotated labels indicating the precise time of each note in every recording, the instrument that plays each note, and the note's position in the metrical structure of the composition. The labels are acquired from musical scores aligned to recordings by dynamic time warping. The labels are verified by trained musicians; we estimate a labeling error rate of 4%. We offer the MusicNet labels to the machine learning and music communities as a resource for training models and a common benchmark for comparing results.\r\n\r\nSource: [MusicNet](https://homes.cs.washington.edu/~thickstn/musicnet.html)","description_withheld":null,"homepage":"https://zenodo.org/record/5120004#.Yhxr0-jMJBA","introduced_date":"2016-11-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-features-of-music-from-scratch","title":"Learning Features of Music from Scratch","first_author":"John Thickstun","url":null},"license":{"name":"Custom","url":"https://homes.cs.washington.edu/~thickstn/musicnet.html"},"modalities":[{"name":"Midi","url":"/datasets/modality/midi"},{"name":"Music","url":"/datasets/modality/music"}],"tasks":[{"name":"Music Transcription","url":"/task/music-transcription","datasets_with_task":"/datasets/task/music-transcription"}],"languages":[],"variants":["MusicNet"],"data_loaders":[],"num_papers_in_archive":43,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/music-transcription-on-musicnet","task":"Music Transcription","dataset_variant":"MusicNet","rows":6,"metrics":["APS","Number of params"],"first_row_in_archive_order":{"model":"Residual Shuffle-Exchange network","paper":"/paper/residual-shuffle-exchange-networks-for-fast","metrics":{"APS":"78.02","Number of params":"3.06M"},"code_links":[{"title":"LUMII-Syslab/RSE","url":"https://github.com/LUMII-Syslab/RSE"},{"title":"Aroksak/RSE","url":"https://github.com/Aroksak/RSE"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/residual-shuffle-exchange-networks-for-fast","title":"Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences","date":"2020-04-06","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/complex-transformer-a-framework-for-modeling","title":"Complex Transformer: A Framework for Modeling Complex-Valued Sequence","date":"2019-10-22","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deep-complex-networks","title":"Deep Complex Networks","date":"2017-05-27","rows_on_this_dataset":2,"code_links":9,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":3,"samples_unverified":3,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-features-of-music-from-scratch","title":"Learning Features of Music from Scratch","date":"2016-11-29","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":11,"samples_ran":4,"samples_unverified":7,"pointer_only_for_licence":3,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}