{"url":"/dataset/dx7-timbre-dataset","name":"DX7 Timbre Dataset","full_name":null,"description_markdown":"This is a dataset of 22.5 hours of synthesized audio using the open-source learnfm clone of the DX7 FM synthesizer, based upon 31K presets from Bobby Blue. These represent \"natural'' synthesis sounds---i.e.presets devised by humans.\r\n\r\nThe authors generated 4-second samples playing midi note 69 (A440) with a note-on duration of 3 seconds. For each preset, the authors varied only the velocity, from 1--127, and perceptually normalized the level of each sound. Sounds that were completely identical were removed from the dataset. DX7 FM synthesis is good for this purpose because it doesn't have a noise oscillator. Thus, for a particular preset, there is a timbral variation as the velocity increases. 8K presets had only one unique sound. The median was 51 unique sound per preset, mean 41.9, stddev 27.4.","description_withheld":null,"homepage":"https://zenodo.org/record/4677102","introduced_date":"2021-04-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/one-billion-audio-sounds-from-gpu-enabled","title":"One Billion Audio Sounds from GPU-enabled Modular Synthesis","first_author":"Joseph Turian","url":null},"license":{"name":"Attribution 4.0 International","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[],"languages":[],"variants":["DX7 Timbre Dataset"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"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."}