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 Electronic Music Fest - Río Grande
Report npuntoend built from the datasets alone
Yes. npuntoend has 1 video listed in datasets used to train and test AI models.
This page only knows about the videos the datasets list. To check every upload on the channel:
video in MusicCaps
A set of 5,521 ten-second music clips from YouTube, each with a written description, that Google published in 2023. It is the standard test set for text-to-music models.
Including Electronic Music Fest - Río Grande
AudioSet 1 videos, 1 rows
Electronic Music Fest - Río Grande
Clip 30s to 40s · Open clip on YouTube · Labels: Drum and bass, House music, Music, Techno, Trance music, Dubstep, Electronic dance music, Dance music, Exciting music
youtube_video wsdH6cv4YkA · row eval:wsdH6cv4YkA:30:40
AudioSeteval
MusicCaps 1 videos, 1 rows
Electronic Music Fest - Río Grande
“The Dance/Electronic song features a repetitive synth keys melody, synth guitar lick, distorted synth bass that perfectly complements the "4 on the floor" kick pattern, punchy snare hits layered with claps, simple "2 step" hi hat pattern, shimmering shakers, repetitive, pulsating synth pad chord progression and groovy synth keys chord progression. At the end of the first part of the loop, there is a short, reversed crash riser, where the drums subtly fade out, followed by energetic crash at the beginning of the second part of the loop, where the drums are brought back again. It sounds energetic and like something you would hear in clubs during the 00s.”
Clip 30s to 40s · Open clip on YouTube
youtube_video wsdH6cv4YkA · row wsdH6cv4YkA:30:40
MusicCaps
What this means
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.
- DLA Piper: Creation of music with generative AI may be copyright infringement (GEMA v Suno, LG München I, 42 O 763/25), 2026-08-28
- Music Business Worldwide: Warner Music Group settles with Suno, strikes first-of-its-kind deal, 2025-11-25
- Music Ally: Suno signs another music licensing deal, with BMG, 2026-08-12
- Music Business Worldwide: Suno inks global deal with Believe, 2026-09-08
What you can do
3 routes. None is a guarantee.
- UK, PRS members. Send PRS for Music your report and ask what collective or licensing route covers your works.
- Germany, GEMA members. GEMA won a first-instance ruling against Suno on 31 July 2026 and has a licensing model. Ask how they apply to your repertoire.
- Signed to Warner, BMG or Believe/TuneCore. Each has an opt-in licensing deal with Suno. Ask your label what opting in or out means for you and whether any settlement money reaches artists.
Keep a copy
Provenance
JSON export SHA-256 8434494f3bb00fd02f03ca4e7768b230a2877ef5af9330a40b1a2a4eedc58570
Dataset versions indexed
| 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.