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

Link: https://entertainment.slashdot.org/story/25/0...

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 Aurelien Herault 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.

Read more of this story at Slashdot.

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