How the Music Industry is Building the Tech to Hunt Down AI-Generated Songs

The goal isn't to stop generative music, but to make it traceable, reports the Verge — 'to identify it early, tag it with metadata, and govern how it moves through the system....'

'Detection systems are being embedded across the entire music pipeline: in the tools used to train models, the platforms where songs are uploaded, the databases that license rights, and the algorithms that shape discovery.'

Platforms like YouTube and [French music streaming service] Deezer have developed internal systems to flag synthetic audio as it's uploaded and shape how it surfaces in search and recommendations. Other music companies — including Audible Magic, Pex, Rightsify, and SoundCloud — are expanding detection, moderation, and attribution features across everything from training datasets to distribution... Vermillio and Musical AI are developing systems to scan finished tracks for synthetic elements and automatically tag them in the metadata. Vermillio's TraceID framework goes deeper by breaking songs into stems — like vocal tone, melodic phrasing, and lyrical patterns — and flagging the specific AI-generated segments, allowing rights holders to detect mimicry at the stem level, even if a new track only borrows parts of an original. The company says its focus isn't takedowns, but proactive licensing and authenticated release... A rights holder or platform can run a finished track through [Vermillo's] TraceID to see if it contains protected elements — and if it does, have the system flag it for licensing before release.

Some companies are going even further upstream to the training data itself. By analyzing what goes into a model, their aim is to estimate how much a generated track borrows from specific artists or songs. That kind of attribution could enable more precise licensing, with royalties based on creative influence instead of post-release disputes...

Deezer has developed internal tools to flag fully AI-generated tracks at upload and reduce their visibility in both algorithmic and editorial recommendations, especially when the content appears spammy. Chief Innovation Officer Aurélien Hérault says that, as of April, those tools were detecting roughly 20 percent of new uploads each day as fully AI-generated — more than double what they saw in January. Tracks identified by the system remain accessible on the platform but are not promoted... Spawning AI's DNTP (Do Not Train Protocol) is pushing detection even earlier — at the dataset level. The opt-out protocol lets artists and rights holders label their work as off-limits for model training.

Thanks to long-time Slashdot reader SonicSpike for sharing the article.

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