HughXuechen/fsd50k-cc0-curated-v1
FSD50K CC0 Curated v1 A 1,408-clip CC0-only subset of FSD50K (Fonseca et al., 2022), curated for an RNN/LSTM audio generation teaching assignment. Contents 1,408 WAV files from the FSD50K dev split (<file_id>.wav) fsd50k_cc0_dev_curated_v1_manifest.csv — per-clip metadata All files are CC0 / public domain — no attribution required 18 primary labels covering music instruments and nature ambient sounds Total size: ~1.5 GB, total duration: ~4.73 hours Original… See the full description on the dataset page: https://huggingface.co/datasets/HughXuechen/fsd50k-cc0-curated-v1.
FSD50K CC0 Curated v1
A 1,408-clip CC0-only subset of FSD50K (Fonseca et al., 2022), curated for an RNN/LSTM audio generation teaching assignment.
Contents
- 1,408 WAV files from the FSD50K dev split (
<file_id>.wav) fsd50k_cc0_dev_curated_v1_manifest.csv— per-clip metadata- All files are CC0 / public domain — no attribution required
- 18 primary labels covering music instruments and nature ambient sounds
- Total size: ~1.5 GB, total duration: ~4.73 hours
- Original sample rates and durations preserved (no resampling or truncation)
Manifest columns
Curation
Clips were selected from the 14,959 CC0 dev files using:
- Exclude-label filter (speech, vehicles, household noise, etc.)
- Keep-label requirement (music + nature ambient categories)
- Duration threshold ≥ 4.17 s (with 6 anchor clip exceptions)
- Round-robin category-balanced fill to a 1.5 GB ceiling
Seed: 42. Full details in the source repository's doc/DATASET_CURATION_REPORT.md.
Usage
from huggingface_hub import snapshot_download
snapshot_download(repo_id="hughxuechen/fsd50k-cc0-curated-v1", repo_type="dataset", local_dir="data/fsd50k_preprocessed")Citation
Fonseca, E., Favory, X., Pons, J., Font, F., & Serra, X. (2022). FSD50K: An Open Dataset of Human-Labeled Sound Events. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 30, 829–852.
