Speakers are recognized automatically
Dubster finds everyone who speaks, picks the cleanest stretches of each voice with no crosstalk and builds a reference. From then on that voice works in any language.
Rec 00:00:00:00 Dubster Studio
Every voice. Any language. Still yours.
Dubster dubs any video into new languages in the speaker's own voice. Background music, sound effects and the feel of the room stay exactly as recorded.
Maya · voice clone
00:12:44:08
Voice · ES
Music & effects
Track 01 00:04:12:16 The problem
The internet watches together. It just doesn't speak the same language.
Professional dubbing is slow and expensive, so most videos stay in one language. Automatic tools cover the volume, but viewers switch them off within a minute.
One-click auto-dub
- Speech synthesized over everythingMusic and sound effects get crushed along with the voice.
- One stock voice for everyoneThe host and the guest sound like the same narrator.
- Word-for-word translationThe line doesn't fit the moment, so it gets sped up into a rush.
- Dry booth soundA street interview and a home studio come out of the same box.
Dubster
- Only the voice changesSpeech is separated from music and effects, and the original audio bed stays untouched.
- Every speaker keeps their voiceDubster finds each person on the track and clones each voice separately.
- Adapted, not just translatedA language model reads the whole conversation and rewrites each line to fit its timing.
- The voice sits in the same roomReverb and loudness match the acoustics of every shot.
Track 02 00:17:03:02 How it works
Keep the video. Replace only the voice.
The idea is simple: split the sound into layers, rewrite one of them, and put it back so nobody hears the seam.
InputSource audio
SeparationVoice · EN
SeparationMusic & effects
New voiceVoice · ES, cloned
OutputFinal mix
Step 1
Separate
A neural model pulls speech away from music and noise. The background is set aside untouched.
Step 2
Listen
Every word is transcribed with exact timing, and we know who said it.
Step 3
Adapt
Translation with the context of the whole video, each speaker's tone and a glossary of names. Every line fits its slot.
Step 4
Voice
The speaker's cloned voice delivers the new line with the same intonation and emotion.
Step 5
Mix
Timing, loudness and room acoustics are matched, and the voice goes back onto the original audio bed.
Track 03 00:31:48:21 Technology
The craft of a dubbing studio, built into a system.
Each layer handles one thing viewers notice the moment it's done badly.
Your footage stays yours
The whole system runs on private infrastructure with no third-party cloud APIs. Creators and brands keep full control of their content and their voices.
Every line fits its moment
Original
Literal
Dubster
Same voice, same room
Dubster measures the reverb of the original recording and places the new voice in the same space.
home studioin the carstreet interviewphone call
A whisper stays a whisper
Intonation, stress and emotion carry over from the original line. Excitement sounds like excitement, not like a news anchor.
A human has the final say
Listen to any line, edit the text, regenerate it or lock it. The rest of the video isn't reprocessed, because every layer is cached.
Track 04 00:52:10:05 Product
A whole dubbing studio in one window.
Drop in a file, pick a language and watch the video move through the pipeline. Then review it line by line like a dubbing director.
| Timecode | Speaker | Original | Dub | Status |
|---|---|---|---|---|
| 00:12:40:11 | Maya | Okay, so this is where the magic happens. | Bueno, aquí es donde ocurre la magia. | Approved |
| 00:12:41:20 | Leo | Wait, you built all of this yourself? | Espera, ¿todo esto lo hiciste tú? | Approved |
| 00:12:44:08 | Maya | Every single piece. It started as an empty garage. | Cada pieza. Empezó siendo un garaje vacío. | In review |
| 00:12:49:02 | Narrator | Three months later, the first episode went live. | Tres meses después salió el primer episodio. | Regenerating |
Track 05 01:05:33:14 Why now
Video went global. Dubbing stayed manual.
Voice models have just learned to carry a voice across languages. We're building the studio workflow around them that the models themselves don't have.
Every audience is global
Creators, schools and brands publish for the whole world from day one, but the voice still locks each video to a single language.
The voice is the brand
People follow a person, not a narrator. Keeping the real voice keeps the trust, the personality and the channel.
Content stays with its owner
Unreleased videos and cloned voices are sensitive. Dubster runs privately and never sends material to someone else's cloud.
CreatorsPodcastsOnline coursesBrands & adsGamesCorporate trainingMediaand anyone who speaks on camera
Track 06 01:21:57:09 Our edge
Models change every quarter. Craft stays.
We don't bet on a single neural network. We're building a pipeline where the best model for every language and every voice plugs in without rebuilding the product.
Model-agnostic
Speech synthesis, recognition and translation plug in as modules. When a better model ships, it drops straight into the pipeline.
Every layer is cached
Fix one line and only that line is recomputed. Iterations take minutes instead of another full pass over the video.
A quality loop
Every reviewer edit becomes knowledge about what a good dub sounds like. The system learns from craft, not just from volume.
Private by design
Content, voices and results stay inside the owner's environment. That's the architecture rights holders trust.
For investors 01:47:00:00 Let's talk
Your next video will speak every language.
We're opening our round and looking for partners who understand creators and AI infrastructure. We'll run a live demo on a video of your choice.
founders@dubster.ai