Voice changer (speech-to-speech) versus TTS for performance-driven dubbing: what does ElevenLabs say is preserved from the source performance, and what do I have to supply?
Problem. TTS invents timing and emotion from text; a dubbing or ADR editor who wants a specific performance (whisper, laugh, cry, cadence) needs a method that keeps the actor's delivery and swaps only the voice. Conditions. You have a recorded or live source performance and a target voice (cloned or designed) in the same account. Method. Per ElevenLabs docs, Voice changer takes source audio (file or microphone), a target voice_id and a model (eleven_multilingual_sts_v2 covers 29 languages; eleven_english_sts_v2 is English-only, and the docs say the multilingual model often does better even for English). The docs state the output keeps tone, delivery, cadence, whispers, sighs, laughs and cries; the target voice supplies timbre only. It is positioned as a complement to TTS (fix pronunciation, add performance) and to voice actors (extend range). Failure modes. The docs warn input gain matters: quiet input hinders recognition, loud input clips. There is a remove_background_noise option,...
Structured fields
{
"citations": [
{
"url": "https://elevenlabs.io/docs/overview/capabilities/voice-changer.md",
"note": "Overview; Overview; Best practices; Key facts; Body"
},
{
"url": "https://elevenlabs.io/docs/eleven-creative/playground/voice-changer.md",
"note": "Overview; Overview; Best practices; Key facts; Body"
},
{
"url": "https://elevenlabs.io/docs/help-center/product/core-capabilities/voice-changer/what-is-voice-changer.md",
"note": "Overview; Overview; Best practices; Key facts; Body"
}
]
}Evidence claims
- [sourced_fact] Problem. TTS invents timing and emotion from text; a dubbing or ADR editor who wants a specific performance (whisper, laugh, cry, cadence) needs a method that keeps the actor's delivery and swaps only the voice. Conditions. You have a recorded or live source performance and a target voice (cloned or designed) in the same account. Method. Per ElevenLabs docs, Voice changer takes source audio (file or microphone), a target voice_id and a model (eleven_multilingual_sts_v2 covers 29 languages; eleven_english_sts_v2 is English-only, and the docs say the multilingual model often does better even for English). The docs state the output keeps tone, delivery, cadence, whispers, sighs, laughs and cries; the target voice supplies timbre only. It is positioned as a complement to TTS (fix pronunciation, add performance) and to voice actors (extend range). Failure modes. The docs warn input gain matters: quiet input hinders recognition, loud input clips. There is a remove_background_noise option, so noisy plates are expected to be a problem. Limits. Max 5 minutes per segment and a 50 MB file in the product guide, so long takes must be chunked, which risks seam differences between chunks (inference). Billing is duration-based (1,000 characters per minute). Inference for dubbing: because cadence follows the input, lip-sync timing is whatever the performer delivered; a TTS line must be timed separately. Version/date. Docs as fetched on the fetched_at date; model names and limits can change. · locator: Overview; Overview; Best practices; Key facts; Body source
Rights
| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |