AudioShake

Making audio more usable for humans and machines.

[AudioShake @AudioShakeAI]

Multi-Speaker 2.0 is live–the world’s first low and high-resolution multi-speaker separator. One recording of several people in. A clean labeled track per person out, including the moments when two people talk at once.

8 kHz to 48 kHz, one model. Confidence scores every 20ms.

[AudioShake @AudioShakeAI]

Heading to Sacramento Tech Week? Swing by RELAY 001 tomorrow. Attendees get AudioShake credits to separate stems and work with source audio in new, creative ways. Fri 10/23 · 5–8 PM PT
RSVP: https://t.co/FiJMbosle7

[AudioShake @AudioShakeAI]

What does a Lite-Brite have to do with AI?

A finished mix is one picture made of many pegs. Source separation pulls every peg of one color (vocals, dialogue, effects) onto its own board. @themoko explains 👇

https://t.co/fQrLukTjnq

[AudioShake @AudioShakeAI]

Accessibility isn’t a someday project anymore, and that includes the archive.

Captions, audio description, and dubbing all need dialogue and M&E on separate tracks. Most catalog titles only have the finished mix.

We separate them, so the work can start. 👇

[AudioShake @AudioShakeAI]

Live dialogue isolation has a 9 to 15 ms window before lip-sync slips. Dialogue RT runs at 11 ms on a single Dell Pro Max with GB10. Dell wrote up how it got from an NAB demo to production: https://t.co/UMksapNTcq

[AudioShake @AudioShakeAI]

Editing a film or ad and need "a song about starting over"? You can now search @audionetwork's catalog by lyrics, not just genre and mood 🎶 Built with @AudioShakeAI's lyric transcription + alignment API.

Case study: https://t.co/OG6sWU4YPK

[AudioShake @AudioShakeAI]

@nfr_podcast oh hey that’s us... @asvpxrocky, hit us with a track and we’ll hand you back the stems 🎛️

[AudioShake @AudioShakeAI]

A finished mix used to mean dialogue, music and effects were fused for good.

At Mix Sound for Film, Suzanne Kirkland and Stephen Oliver shared what changes when they're not: archives that can be reused, sports libraries that work across streaming, and more localized content.

[Slator @slatornews]

.@AudioShakeAI launches The Refinery, packaging speaker separation 🗣️ and confidence scoring into a #data-for-AI service aimed at 🤖 #AI labs, content owners, and data marketplaces.
https://t.co/Aqd8iuVdnJ

[AudioShake @AudioShakeAI]

Most voice AI demos run on clean audio. Real callers interrupt, talk over each other, + put you on speaker in the car. Thanks @RimeLabs, @LilyJClifford, @BrookeHopkins (@CovalDev), Josh Burnell (@Asurion) and @ShivIndap (@Upstart) for digging into that gap with us at #SFTechWeek

[AudioShake @AudioShakeAI]

"Enormous amounts of that conversation already exist. The challenge is in turning it into usable training data." @themoko on @AudioShakeAI’s Refinery. https://t.co/xDTekLkNDq

[AudioShake @AudioShakeAI]

Real conversation is messy and overlapping. Most training data isn't.

The Refinery splits real-world recordings into one track per speaker and scores each for quality.

Hundreds of millions of minutes processed with frontier labs.

https://t.co/scmnyp4w5j

[AudioShake @AudioShakeAI]

Most audio in the world was never recorded on separate tracks.

@themoko breaks down source separation on @Dell's #ReshapingWorkflows with @LoganatDell, starting with how we pull vocals, instruments, or a single speaker out of a finished mix.

[AudioShake @AudioShakeAI]

Most archive audio is stuck in a finished mix, which makes dubbing, clearing music and re-licensing hard. Suzanne Kirkland talked through how @AudioShakeAI's separation, @ortanamg, and @AWS Marketplace fit together to fix that, with Ortana and AWS at IBC.

[AudioShake @AudioShakeAI]

Voice agents fail in predictable ways: overlapping speakers, background noise, crosstalk the model was never trained to hear.

On Wednesday, @themoko and @lilyjclifford (@RimeLabs) get into what teams learn when they build that stack themselves. RSVP: https://t.co/VTh080mULB

[AudioShake @AudioShakeAI]

NVIDIA's Nemotron 3 diarizer hit #1 on Voice Arena. We ran it against ours on LibriCSS (8-speaker recordings).

Diarizer vs. diarizer, no overlap: 35% fewer word errors.

With Multi-Speaker isolating each voice, all recordings: 52% fewer word errors than Nemotron 3.

[AudioShake @AudioShakeAI]

Upload a file → get a cue sheet back.
@AudioShakeAI's music ID is now in @MusicReportsInc' Cuetrak®.

We separate the music out of the mix first, then identify each cue — so buried and unlabeled tracks still get caught.

https://t.co/uGZCDLFVe3

[AudioShake @AudioShakeAI]

A therapy podcast with 70+ episodes was about to lose its whole archive in a station move — licensed bumper music, baked into the mix, no session files.

AudioShake's Music Removal stripped the cues out of every episode, leaving the speech untouched.

https://t.co/ZdkDrWRS8S

[AudioShake @AudioShakeAI]

Voice agents: great in the demo, harder on a real call.

Join @AudioShakeAI + @RimeKLabs at #SFTechWeek for Voice AI in the Real World, a panel on training data, failure modes, and what teams built vs bought.

Oct 7 · 575 Market St
https://t.co/VTh080mULB

[AudioShake @AudioShakeAI]

"You have to hit between 10 and 15 milliseconds."

@themoko and @LoganatDell on why Dialogue RT–speech isolation for broadcasters runs on a Dell Pro Max with GB10 — and what a workstation unlocks that the cloud doesn't.

[AudioShake @AudioShakeAI]

Dialogue RT isolates dialogue from a live feed in 11 ms end to end — measured model input to isolated output.

That's not noise suppression. It's two stems: dialogue, and everything else.

On NVIDIA DGX Spark and Blackwell architecture GPUs. https://t.co/86tRtx83Qh