{"url":"/dataset/fsdkaggle2018","name":"FSDKaggle2018","full_name":"FSDKaggle2018","description_markdown":"**FSDKaggle2018** is an audio dataset containing 11,073 audio files annotated with 41 labels of the AudioSet Ontology. FSDKaggle2018 has been used for the DCASE Challenge 2018 Task 2. All audio samples are gathered from Freesound and are provided as uncompressed PCM 16 bit, 44.1 kHz mono audio files. The 41 categories of the AudioSet Ontology are:\n\"Acoustic_guitar\", \"Applause\", \"Bark\", \"Bass_drum\", \"Burping_or_eructation\", \"Bus\", \"Cello\", \"Chime\", \"Clarinet\", \"Computer_keyboard\", \"Cough\", \"Cowbell\", \"Double_bass\", \"Drawer_open_or_close\", \"Electric_piano\", \"Fart\", \"Finger_snapping\", \"Fireworks\", \"Flute\", \"Glockenspiel\", \"Gong\", \"Gunshot_or_gunfire\", \"Harmonica\", \"Hi-hat\", \"Keys_jangling\", \"Knock\", \"Laughter\", \"Meow\", \"Microwave_oven\", \"Oboe\", \"Saxophone\", \"Scissors\", \"Shatter\", \"Snare_drum\", \"Squeak\", \"Tambourine\", \"Tearing\", \"Telephone\", \"Trumpet\", \"Violin_or_fiddle\", \"Writing\".\n\nSource: [https://zenodo.org/record/2552860](https://zenodo.org/record/2552860)\nImage Source: [https://labs.freesound.org/datasets/](https://labs.freesound.org/datasets/)","description_withheld":null,"homepage":"https://zenodo.org/record/2552860","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/general-purpose-tagging-of-freesound-audio","title":"General-purpose Tagging of Freesound Audio with AudioSet Labels: Task Description, Dataset, and Baseline","first_author":"Eduardo Fonseca","url":null},"license":{"name":"Other (Attribution)","url":"https://zenodo.org/record/2552860"},"modalities":[{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Multi-Task Learning","url":"/task/multi-task-learning","datasets_with_task":"/datasets/task/multi-task-learning"},{"name":"Few-Shot Audio Classification","url":"/task/few-shot-audio-classification","datasets_with_task":"/datasets/task/few-shot-audio-classification"},{"name":"Audio Tagging","url":"/task/audio-tagging","datasets_with_task":"/datasets/task/audio-tagging"}],"languages":[],"variants":["FSDKaggle2018"],"data_loaders":[],"num_papers_in_archive":12,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/few-shot-audio-classification-on","task":"Few-Shot Audio Classification","dataset_variant":"FSDKaggle2018","rows":10,"metrics":["Top-1 Accuracy(5-Way-1-Shot)"],"first_row_in_archive_order":{"model":"MAML (CRNN)","paper":"/paper/metaaudio-a-few-shot-audio-classification","metrics":{"Top-1 Accuracy(5-Way-1-Shot)":"43.45 +- 0.46"},"code_links":[{"title":"cheggan/metaaudio-a-few-shot-audio-classification-benchmark","url":"https://github.com/cheggan/metaaudio-a-few-shot-audio-classification-benchmark"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mt-slvr-multi-task-self-supervised-learning","title":"MT-SLVR: Multi-Task Self-Supervised Learning for Transformation In(Variant) Representations","date":"2023-05-29","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/metaaudio-a-few-shot-audio-classification","title":"MetaAudio: A Few-Shot Audio Classification Benchmark","date":"2022-04-05","rows_on_this_dataset":7,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"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."}