---
license: cc0-1.0
task_categories:
  - audio-classification
tags:
  - audio
  - audio-generation
  - fsd50k
  - rnn
  - music
  - ambient
size_categories:
  - 1K<n<10K
---

# FSD50K CC0 Curated v1

A 1,408-clip CC0-only subset of [FSD50K](https://zenodo.org/record/4060432) (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

| Column | Description |
|--------|-------------|
| `file_id` | FSD50K numeric ID — matches WAV filename |
| `wav_path` | Original local path (ignore — use `file_id` to locate files) |
| `split` | Train / val / test assignment (stratified by `primary_label`, seed=42) |
| `license_raw` | Original Freesound license URL |
| `license_normalized` | Always `CC0` in this subset |
| `labels` | Comma-separated FSD50K labels |
| `primary_label` | Single label used for stratification (first keep-label match) |
| `tags` | Freesound user tags |
| `size_bytes` | WAV file size in bytes |
| `duration_sec` | Clip duration in seconds |

## Curation

Clips were selected from the 14,959 CC0 dev files using:
1. Exclude-label filter (speech, vehicles, household noise, etc.)
2. Keep-label requirement (music + nature ambient categories)
3. Duration threshold ≥ 4.17 s (with 6 anchor clip exceptions)
4. 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

```python
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.