Making audio more usable for humans and machines.
San Francisco
Joined October 2019
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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: audioshake.ai/case-studies/u…
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.
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
"Enormous amounts of that conversation already exist. The challenge is in turning it into usable training data." @themoko on @AudioShakeAI’s Refinery. audioshake.ai/products/refin…
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.
audioshake.ai/products/refin…
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.
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.
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: partiful.com/e/qRX76YKI93J2I…
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.
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.
audioshake.ai/press-releases…
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.
audioshake.ai/case-studies/f…
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
partiful.com/e/qRX76YKI93J2I…
"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.
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. audioshake.ai/post/isolating…
Real conversation isn't tidy. People interrupt, agree over each other, laugh through the answer.
This is the part every other tool gives up on. Multi-Speaker 2.0 keeps both voices as separate tracks, tells you how confident it is, and runs on anything from 8 to 48 kHz.
Four days at IBC, hundreds of conversations. The question we heard most:
“Can it run on the feed, not the file?”
Answer: yes. Live, less than 11 milliseconds. Another great year in the books.
Most audio in the world was never recorded on separate tracks.
Jessica Powell breaks down source separation on Dell's #ReshapingWorkflows — how we pull vocals, instruments, or a single speaker out of a finished mix.
Full episode: podcasts.apple.com/us/podcas…