Voice is the part of adult AI that hosted vendors police most strictly, which makes open-weights TTS the only workable route. Higgs Audio is the model we run: zero-shot cloning from a short clip, expressive delivery, and no filter on what it says. Here is how it sounds, how it clones, and where it still falls short of ElevenLabs.
Short answer: Higgs Audio is the reason uncensored character voice exists as a product feature. It is open weights, it clones a voice from a few seconds of reference audio, it delivers emotion rather than reading, and because it runs on your own hardware there is no policy layer deciding what it may say. It is not as polished as ElevenLabs on clean narration, and it needs care with long inputs and with cloning consent. MyBabes runs it for character voice messages and cloned voices; ElevenLabs is used only where its policy allows.
Why voice is the hard part
Image and video vendors filter explicit content; voice vendors filter it harder and enforce at the account level, because a cloned voice saying explicit things is the scenario their legal teams fear most. Every major hosted TTS service prohibits sexually explicit content in its terms and moderates generated speech. For an adult chat product that wants a persona to send voice messages, that leaves exactly one route: an open-weights model, self-hosted.
What Higgs Audio is
Higgs Audio is Boson AI’s open-weights text-to-speech model family. Relevant properties:
Zero-shot voice cloning. A reference clip of a few seconds is enough to reproduce a voice; no training run.
Expressive delivery. It infers emotion from text and context rather than reading flat, which matters more in intimate speech than anywhere else.
Multi-speaker and long-form modes for dialogue and narration.
No content filter. The model has none; whatever moderation exists is whatever you add.
How it compares with ElevenLabs
Higgs Audio (self-hosted) | ElevenLabs (hosted) | |
|---|---|---|
Explicit content | No restriction | Prohibited by terms; moderated |
Naturalness on clean narration | Good | Best available |
Emotional delivery in intimate speech | Very good | Very good where permitted |
Voice cloning | Zero-shot, seconds of audio | Instant and professional cloning, policy-gated |
Languages | Strong in English, decent in major European languages | Very broad |
Latency | Depends on your GPU; near real-time on a modern card | Low |
Cost at scale | Hardware only | Per character, adds up fast |
Failure modes | Occasional mispronunciation, drift on very long inputs | Refusals, account risk |
On clean, non-explicit narration ElevenLabs is still slightly more natural. On the material an adult product actually needs, the comparison is not close, because one of the two will not produce it. Our ElevenLabs analysis covers what it can be used for.
Cloning: what works
We cloned 30 voices from reference clips of 5 to 30 seconds and rated similarity and stability.
Reference length. 10–15 seconds of clean speech gave the best similarity; longer clips did not help, shorter ones lost timbre.
Reference quality. Background noise and music in the reference transfer into the clone. Use dry, close-mic audio.
Emotional range of the reference. A reference with some expression clones better than a flat one; the model generalises the timbre and keeps the expressiveness.
Stability. Cloned voices held across hundreds of generations; no drift between messages.
Consent is not a technical topic but it is the one that matters: cloning a real person’s voice without permission is off limits on MyBabes, and the voices offered are either synthetic or licensed. The same rule we apply to likeness in images applies to voice.
Where it falls short
Long inputs. Past roughly a minute of generated speech in one pass, pacing drifts. Chunk long passages.
Mispronunciations. Names and rare words need phonetic spelling in the input.
Whispers and breath. Intimate registers that rely on whisper and breath are good but not yet at the level of the best hosted voices.
Hardware. Near real-time generation needs a current GPU; on older cards voice messages take several seconds.
Using it in a chat product
The pattern on MyBabes: the persona’s chat model writes the message, a short post-process adds delivery cues, Higgs renders it in the character’s voice, and the audio is delivered as a voice message. Because the model is self-hosted, the voice says what the persona says, in character, with no second model deciding whether it is allowed to.
Setting it up: what a working deployment looks like
Higgs Audio is a model, not a service, so the deployment decides how it performs. The pieces that mattered in our setup:
Serving. A dedicated GPU worker that keeps the model resident; loading per request is far too slow. One modern 24 GB card handles a steady stream of short voice messages; batch generation of long narration wants more.
Reference library. Each character has a stored reference clip (10–15 seconds, dry, expressive) and a cached speaker embedding, so cloning cost is paid once, not per message.
Text preprocessing. Names and rare words are rewritten phonetically, long passages are chunked at sentence boundaries, and short delivery cues (a pause, a laugh, a whisper marker) are inserted by the chat model before synthesis.
Post-processing. Loudness normalisation and a gentle de-esser; the raw output is slightly hot on sibilants for some voices.
Caching. Identical text plus voice produces identical audio; greetings and stock lines are cached.
None of this is exotic, but skipping any one of them shows up in the product: cold-start delays, mispronounced names, or a voice that sounds different from message to message.
Voice quality by register
Not every kind of speech comes out equally well. From listening tests across characters:
Register | Quality | Notes |
|---|---|---|
Conversational, upbeat | Very good | The model’s sweet spot |
Intimate, low volume | Good | Breath is convincing; whisper slightly synthetic |
Narration, long passages | Good with chunking | Pacing drifts without it |
Emotional peaks (anger, excitement) | Good | Occasional over-acting; tone cues help |
Non-English | Decent in major languages | Accent can drift toward English on rare words |
How it compares with other open TTS models
The open TTS field moved fast in 2025–2026. Against the alternatives we tried, Higgs stood out for zero-shot cloning fidelity and emotional delivery; some competitors were faster, a few were more stable on very long inputs, none combined all three as well. For a product where the voice has to sound like a specific character saying something intimate, cloning fidelity and expressiveness are the properties that matter, and that is why it is the engine behind the character voices on MyBabes.
Related in the Lab
Key takeaways
Hosted TTS vendors prohibit explicit content; open-weights TTS is the only route for adult voice.
Higgs Audio clones from seconds of audio, delivers with emotion, and has no content filter.
ElevenLabs is slightly more natural on clean narration and unusable for explicit speech.
Use 10–15 seconds of dry reference audio; chunk long passages; never clone without consent.
FAQ
Is Higgs Audio uncensored?
The model has no content filter. Whatever restrictions apply come from the service running it.
Can Higgs Audio clone a voice?
Yes, zero-shot from a short reference clip. Around 10–15 seconds of clean speech works best.
Is Higgs Audio better than ElevenLabs?
For explicit adult content, Higgs works and ElevenLabs does not. For clean narration, ElevenLabs is still slightly more natural.
What hardware does Higgs Audio need?
A modern GPU for near real-time generation; it runs on smaller cards with longer generation times.
Last tested: August 2026.
Models covered
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MyBabes runs Wan 2.7, Seedance 2.0 and Krea inside its own generation stack, so the prompts refused on official apps generate as written. No GPU, no setup.
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Jiri builds MyBabes and runs the Lab’s model testing: the same prompt set on every image, video and chat model, on the vendor’s official surface and on MyBabes, re-run after every release. He writes up what the models actually do, not what the launch posts say.
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