{"url":"/dataset/idmt-smt-bass","name":"IDMT-SMT-Bass","full_name":null,"description_markdown":"The IDMT-SMT-Bass database is a large database for automatic bass transcription and signal processing.\r\nThe overall duration of the audio material is approx. 3.6 hours.\r\nThe dataset consists of approx. 4300 WAV files (44.1 kHz, 24bit) with single recorded notes.\r\nOverall, 10 different bass-related playing techniques namely 5 plucking styles\r\nfingerstyle (FS)\r\npicked (PK)\r\nmuted (MU)\r\nslap-thumb (ST)\r\nslap-pluck (SP)\r\nand 5 expression styles\r\nnormal (NO)\r\nvibrato (VI)\r\nbending (BE)\r\nharmonics (HA)\r\ndead-note (DN)\r\nare incorporated. A further explaination of the playing techniques is provided in [1].\r\n\r\nFor each of the three expression techniques (vibrato, bending, slide), two subclasses were defined in [2]:\r\nfast vibrato, slow vibrato\r\nsemi-tone bending, quarter-note bending\r\nslide up, slide down (recorded with fretless bass guitar)\r\n3 different 4-string electric bass guitars, each with 3 different pick-up settings were used for recording.\r\n\r\nThe notes cover the common pitch range of a 4-string bass guitar from E1 (41.2 Hz) to G3 (196.0 Hz).","description_withheld":null,"homepage":"https://www.idmt.fraunhofer.de/en/publications/datasets/bass.html","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CCBY","url":"https://zenodo.org/records/7188892"},"modalities":[],"tasks":[],"languages":[],"variants":["IDMT-SMT-Bass"],"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."}