Report effettidiclara built from the datasets alone
This page only knows about the videos the datasets list. To check every upload on the channel:
video in AudioSet
A list of about a million ten-second YouTube clips, each labelled with the sounds in it, that Google published in 2017. Labs use it to train and test general audio and music models.
Including REBECCA - analog spring reverb - effettidiclara - PROMO #4
Clip 40s to 50s · Open clip on YouTube · Labels: Guitar, Music, Musical instrument, Telephone bell ringing
youtube_video fpfPPdYA05s · row unbalanced_train:fpfPPdYA05s:40:50
AudioSetunbalanced_train
Last reviewed 2026-09-24.
Presence in a public research dataset shows that a clip of your recording was listed by academic or industry researchers as material for building or testing audio models. It does not by itself show which commercial products, if any, used the clip. The legal picture is moving. On 31 July 2026 the Regional Court of Munich I ruled in GEMA's case against Suno (case 42 O 763/25) that reproducing works for training, holding them in a model in retrievable form, and generating similar outputs can each infringe copyright under German and EU law; the judgment is not final and can be appealed. In the United States, Warner Music Group settled its claims against Suno on 25 November 2025 with a licensing deal, while the parallel claims by Universal and Sony were still pending at that point. Since then BMG (12 August 2026) and Believe/TuneCore (8 September 2026) have signed opt-in licensing deals with Suno.
3 routes. None is a guarantee.
JSON export SHA-256 3b4f93d94ad8d259b8729f007d061d83ea094fa6d9a6b093e7c81805add9191a
| Dataset | File | Rows | Loaded | SHA-256 |
|---|---|---|---|---|
| audioset | balanced_train_segments.csv | 8,836 | 2026-09-24T10:30:36+00:00 | 3b83e5ff9ed72cfd… |
| audioset | eval_segments.csv | 7,848 | 2026-09-24T10:30:36+00:00 | f7055f53935f70e7… |
| audioset | unbalanced_train_segments.csv | 1,063,333 | 2026-09-24T10:30:43+00:00 | bb2dfd5e4f1ced39… |
| laion_disco_12m | train-00000-of-00005.parquet | 2,464,184 | 2026-09-24T12:18:19+00:00 | f8b1f0034f8f1e94… |
| laion_disco_12m | train-00001-of-00005.parquet | 2,464,183 | 2026-09-24T12:32:29+00:00 | 71d78ad14ee3f85d… |
| laion_disco_12m | train-00002-of-00005.parquet | 2,464,183 | 2026-09-24T12:49:06+00:00 | 0feba570a0e8e73c… |
| laion_disco_12m | train-00003-of-00005.parquet | 2,464,183 | 2026-09-24T13:06:37+00:00 | 21a77d99fd85ad2f… |
| laion_disco_12m | train-00004-of-00005.parquet | 2,464,183 | 2026-09-24T13:24:36+00:00 | 6ac5f59958b6b813… |
| musiccaps | musiccaps-public.csv | 5,521 | 2026-09-24T10:29:42+00:00 | 8cc109ac507b5e5a… |
These pages report where identifiers from public research datasets point. Presence in a dataset is a fact about the dataset, not a claim about the channel or artist, and says nothing about what any company did with the material. This report is informational and is not legal advice. It shows that identifiers matching your work are present in the named public research datasets; it does not establish how any particular company used them. If you are the subject of this page and want it removed, see removals.