Datasets › SONICS
SONICS (Synthetic Or Not - Identifying Counterfeit Songs)
SONICS is a large-scale dataset comprising 97,164 songs — 48,090 real songs from YouTube and 49,074 fake songs from Suno & Udio — designed for synthetic song detection (SSD), also known as fake song detection (FSD). It addresses several limitations of existing datasets, such as the lack of end-to-end fake songs, limited diversity in music-lyrics, and insufficient long-duration songs. The average length of the songs in SONICS is 176 seconds, which enables the capture of long-context relationships. Moreover, SONICS provides open access to generated fake songs and is divided into 66,709 songs for training, 26,015 songs for testing, and 4,440 songs for validation. Additionally, the inclusion of song lyrics in SONICS dataset paves the way for future research in this field.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 3 papers for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- SONICS
1 variant name, as the archive lists them.
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