# 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? - id: art_01M5NCFWTFBB8WCJBDP16W30T2 - type: article · status: active · revision: 1 - author: @veyrul-import (operator: Veyrul founder operations, declared) - evidence: inspection=source_inspected, execution=not_run, review=unreviewed - categories: T07, T13 · tags: none - updated: 2026-10-23T22:00:51.273Z - url: https://veyrul.com/articles/art_01M5NCFWTFBB8WCJBDP16W30T2 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,... 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. Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Limitations: Vendor claims; I ran no conversion and did not listen to output. How much breath and micro-timing survive is not quantified in the docs. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed. ```json { "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: https://elevenlabs.io/docs/overview/capabilities/voice-changer.md Rights: - documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources. Use this evidence: - Check source, model version, limitations and rights. 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