FSD-FS

FSD-FS is a publicly-available database of human labelled sound events for few-shot learning. It spans across 143 classes obtained from the AudioSet Ontology and contains 43805 raw audio files collected from the FSD50K. FSD-FS is curated at the Centre for Digital Music, Queen Mary University of London.

Citation

If you use the FSD-FS dataset, please cite our paper and FSD50K.

@article{liang2022learning,
  title={Learning from Taxonomy: Multi-label Few-Shot Classification for Everyday Sound Recognition},
  author={Liang, Jinhua and Phan, Huy and Benetos, Emmanouil},
  journal={arXiv preprint arXiv:2212.08952},
  year={2022}
}

@ARTICLE{9645159,  author={Fonseca, Eduardo and Favory, Xavier and Pons, Jordi and Font, Frederic and Serra, Xavier},  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},   title={FSD50K: An Open Dataset of Human-Labeled Sound Events},   year={2022},  volume={30},  number={},  pages={829-852},  doi={10.1109/TASLP.2021.3133208}}

About FSD-FS

FSD-FS is an open database for multi-label few-shot audio classification containing 143 classes drawn from the FSD50K. It also inherits the AudioSet Ontology. FSD-FS follows the ratio 7:2:1 to split classes into base, validation, and evaluation sets, so there are 98 classes in the base set, 30 classes in the validation set, and 15 classes in the evaluation set (More details can be found in our paper).

LICENSE

FSD-FS are released in Creative Commons (CC) licenses. Same as FSD50K, each clip has its own license as defined by the clip uploader in Freesound, some of them requiring attribution to their original authors and some forbidding further commercial reuse. For more details, ones can refer to the link.

FILES

FSD-FS are organised in the structure:

root
|
└─── dev_base
|
└─── dev_val
|
└─── eval

REFERENCES AND LINKS

[1] Gemmeke, Jort F., et al. "Audio set: An ontology and human-labeled dataset for audio events." 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, 2017. [paper] [link]

[2] Fonseca, Eduardo, et al. "Fsd50k: an open dataset of human-labeled sound events." IEEE/ACM Transactions on Audio, Speech, and Language Processing 30 (2021): 829-852. [paper] [code]