songs in LAION-DISCO-12M under the artist name
A list of 12 million songs on YouTube Music, gathered by walking artist pages, that LAION published in 2024 for training general music models.
Including Feliz Navidad, Folk japonés, Provincia (Remix)
Artist Daniela Spalla on YouTube Music
Yes. Daniela Spalla has 58 songs listed in a dataset used to train AI music models.
Listed under the artist name 58 songs in LAION-DISCO-12M
Matched exactly: this YouTube Music artist id is the one the dataset lists these songs under.
Feliz Navidad
Listed as Daniela Spalla, Santiago En La Guitarra – Feliz Navidad (Feliz Navidad) · Watch on YouTube
youtube_video 7kCn85eGN_Q · row 7kCn85eGN_Q
LAION-DISCO-12M
Folk japonés
Listed as Daniela Spalla – Folk japonés (Folk japonés) · Watch on YouTube
youtube_video 9hPT3Fwm7jk · row 9hPT3Fwm7jk
LAION-DISCO-12M
Provincia (Remix)
Listed as Daniela Spalla, Nico Cotton – Provincia (Remix) (Provincia (Remix)) · Watch on YouTube
youtube_video UpC3B-8TEsI · row UpC3B-8TEsI
LAION-DISCO-12M
Nada Que No Quieras Tú
Listed as Ramona, Daniela Spalla – Nada Que No Quieras Tú (Nada Que No Quieras Tú) · Watch on YouTube
youtube_video XC87JoYKxb4 · row XC87JoYKxb4
LAION-DISCO-12M
Carteles (Versión Acústica)
Listed as Daniela Spalla – Carteles (Versión Acústica) (Puro Teatro (Deluxe)) · Watch on YouTube
youtube_video _Wav6d9vC_M · row _Wav6d9vC_M
LAION-DISCO-12M
Canción Decente (Versión Acústica)
Listed as Daniela Spalla – Canción Decente (Versión Acústica) (Sesiones Acústicas) · Watch on YouTube
youtube_video b-3jXoQfllw · row b-3jXoQfllw
LAION-DISCO-12M
Insomnio (En Vivo)
Listed as Daniela Spalla – Insomnio (En Vivo) (Camas Separadas (Edición Especial)) · Watch on YouTube
youtube_video nJwXYsMd5-A · row nJwXYsMd5-A
LAION-DISCO-12M
Insomnio (Versión Acústica)
Listed as Daniela Spalla – Insomnio (Versión Acústica) (Sesiones Acústicas) · Watch on YouTube
youtube_video nw-dVB_snQ4 · row nw-dVB_snQ4
LAION-DISCO-12M
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.
Is this you?
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. If you are this artist and want this page removed, see removals.