FSDKaggle2018: 11k audio clips and 18h of training data unequally distributed in 41 classes of everyday sounds. It was collected for the DCASE2018 Challenge Task2: General-purpose tagging of Freesound audio with AudioSet labels. The dataset is described in our paper General-purpose tagging of Freesound audio with AudioSet labels: task description, dataset, and baseline.
FSDnoisy18k: an audio dataset collected with the aim of fostering the investigation of label noise in sound event classification. It contains 42.5 hours of audio across 20 sound classes, including a small amount of manually-labeled data and a larger quantity of real-world noisy data. Please check its companion site for a detailed dataset description and download, and our ICASSP 2019 paper for an evaluation of noise-robust loss functions using FSDnoisy18k.
FSD: This is the first and main dataset being collected with the Freesound Annotator. It is currently work-in-progress and we hope to make the first release in mid 2019. FSD will be a large-scale, general-purpose audio dataset consisting of tens of thousands of audio clips from Freesound organised using the AudioSet Ontology.