Report Choi, Seung-Joon built from the datasets alone

Yes. Choi, Seung-Joon has 3 videos 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:

Used for training and testing 3

videos 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 Dark Eyes(러시아 민요 - 검은 눈동자), Gao Shan Qing(Taiwan Folksong) 고산청(타이완 민요), 2 Korean Old Pop Songs(흘러간 노래 접속곡)

Used for testing 1

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 Dark Eyes(러시아 민요 - 검은 눈동자)

AudioSet 3 videos, 3 rows

Dark Eyes(러시아 민요 - 검은 눈동자)

Clip 260s to 270s · Open clip on YouTube · Labels: Harmonica, Wind instrument, woodwind instrument

youtube_video 3Nwsd439zmU · row balanced_train:3Nwsd439zmU:260:270

AudioSetbalanced_train

Gao Shan Qing(Taiwan Folksong) 고산청(타이완 민요)

Clip 160s to 170s · Open clip on YouTube · Labels: Harmonica, Wind instrument, woodwind instrument

youtube_video hPLWQtzUtG0 · row unbalanced_train:hPLWQtzUtG0:160:170

AudioSetunbalanced_train

2 Korean Old Pop Songs(흘러간 노래 접속곡)

Clip 30s to 40s · Open clip on YouTube · Labels: Music

youtube_video pgBY2I8iS8A · row unbalanced_train:pgBY2I8iS8A:30:40

AudioSetunbalanced_train

MusicCaps 1 videos, 1 rows

Dark Eyes(러시아 민요 - 검은 눈동자)

“The low quality recording features a live performance of a folk song and it consists of harmonica melodies played over groovy double bass and shimmering hi-hats. The recording is noisy and fairly wide.”

Clip 260s to 270s · Open clip on YouTube

youtube_video 3Nwsd439zmU · row 3Nwsd439zmU:260:270

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.

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.
- PRS for Music and Artificial Intelligence, Version 1 (October 2025), 2025-10-01
- PRS for Music: AI and music copyright, 2026-09-24
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.
- GEMA: Suno AI and OpenAI, GEMA sues for fair compensation, 2025-01-21
- DLA Piper: GEMA v Suno, Munich Regional Court judgment of 31 July 2026, 2026-08-28
- Music Business Worldwide: Germany's GEMA launches AI Charter, 2024-11-05
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.
- Music Business Worldwide: Warner Music Group settles with Suno, 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

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Provenance

JSON export SHA-256 f92f1d1e6898edd6c840d313eca9874641144ef76143abcefb033d62f54824de

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.