ElevenLabs Voice Changer

Transform the voice in an audio recording into a different target voice. Voice Changer (previously called Speech-to-Speech — the API endpoint and SDK methods still use the

speech_to_speech

speechToSpeech

name) keeps the original performance — emotion, pacing, intonation, breaths, whispers, laughs, cries — and only swaps who is speaking.

Setup: See Installation Guide. For JavaScript, use
@elevenlabs/*
packages only.

Key Facts

Maximum input length: 5 minutes per request — split longer recordings into chunks and stitch the outputs.
Maximum file size: 50 MB per request — compress to MP3 if your source is larger.
Pricing: 1,000 characters per minute of audio processed (duration-based, not text-based).
Recommended model:
```
eleven_multilingual_sts_v2
```
— often outperforms
```
eleven_english_sts_v2
```
even for English-only content.

Quick Start

Python

python

from elevenlabs import ElevenLabs

client = ElevenLabs()

with open("source.mp3", "rb") as audio_file:
    audio_stream = client.speech_to_speech.convert(
        voice_id="JBFqnCBsd6RMkjVDRZzb",  # George
        audio=audio_file,
        model_id="eleven_multilingual_sts_v2",
        output_format="mp3_44100_128",
    )

with open("converted.mp3", "wb") as f:
    for chunk in audio_stream:
        f.write(chunk)

JavaScript

javascript

import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createReadStream, createWriteStream } from "fs";

const client = new ElevenLabsClient();

const audioStream = await client.speechToSpeech.convert("JBFqnCBsd6RMkjVDRZzb", {
  audio: createReadStream("source.mp3"),
  modelId: "eleven_multilingual_sts_v2",
  outputFormat: "mp3_44100_128",
});

audioStream.pipe(createWriteStream("converted.mp3"));

cURL

bash

curl -X POST "https://api.elevenlabs.io/v1/speech-to-speech/JBFqnCBsd6RMkjVDRZzb?output_format=mp3_44100_128" \
  -H "xi-api-key: $ELEVENLABS_API_KEY" \
  -F "audio=@source.mp3" \
  -F "model_id=eleven_multilingual_sts_v2" \
  --output converted.mp3

Parameters

Parameter	Type	Default	Description
`voice_id`	string (required)	—	Target voice to speak in. Use a pre-made voice ID, a cloned voice, or a voice from the library
`audio`	file (required)	—	Source audio whose performance (emotion, timing, delivery) will be preserved
`model_id`	string	`eleven_english_sts_v2`	`eleven_multilingual_sts_v2` for 29 languages, `eleven_english_sts_v2` for English-only
`output_format`	string	`mp3_44100_128`	See output formats table below
`voice_settings`	JSON string	—	Override stored voice settings for this request only
`seed`	integer	—	Best-effort deterministic sampling (0 – 4294967295)
`remove_background_noise`	boolean	`false`	Run the isolation model on the input before conversion
`file_format`	string	`other`	`other` for any encoded audio, or `pcm_s16le_16` for 16-bit PCM mono @ 16kHz little-endian (lower latency)
`optimize_streaming_latency`	int (query)	—	0–4. Trade quality for latency. `4` is fastest but disables the text normalizer
`enable_logging`	boolean (query)	`true`	Set to `false` for zero-retention mode (enterprise only — disables history/stitching)

Models

Model ID	Languages	Best For
`eleven_multilingual_sts_v2`	29	Recommended for everything — often outperforms the English model even on English audio
`eleven_english_sts_v2`	English	API default — English-only fallback

Only models whose

can_do_voice_conversion

property is true can be used here. Voice Changer does not currently have a low-latency "flash/turbo" tier — if you need one, keep

pcm_s16le_16

input, an

opus_*

/ low-bitrate

mp3_*

output, and raise

optimize_streaming_latency

Languages (

eleven_multilingual_sts_v2

)

English (US, UK, AU, CA), Japanese, Chinese, German, Hindi, French (FR, CA), Korean, Portuguese (BR, PT), Italian, Spanish (ES, MX), Indonesian, Dutch, Turkish, Filipino, Polish, Swedish, Bulgarian, Romanian, Arabic (SA, AE), Czech, Greek, Finnish, Croatian, Malay, Slovak, Danish, Tamil, Ukrainian, Russian.

Target Voices

Use any voice ID from pre-made voices, your cloned voices, or the voice library.

Popular voices:

```
JBFqnCBsd6RMkjVDRZzb
```
— George (male, narrative)
```
EXAVITQu4vr4xnSDxMaL
```
— Sarah (female, soft)
```
onwK4e9ZLuTAKqWW03F9
```
— Daniel (male, authoritative)
```
XB0fDUnXU5powFXDhCwa
```
— Charlotte (female, conversational)

python

voices = client.voices.get_all()
for voice in voices.voices:
    print(f"{voice.voice_id}: {voice.name}")

Converting from a URL

python

import requests
from io import BytesIO
from elevenlabs import ElevenLabs

client = ElevenLabs()

audio_url = "https://storage.googleapis.com/eleven-public-cdn/audio/marketing/nicole.mp3"
response = requests.get(audio_url)
audio_data = BytesIO(response.content)

audio_stream = client.speech_to_speech.convert(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    audio=audio_data,
    model_id="eleven_multilingual_sts_v2",
    output_format="mp3_44100_128",
)

with open("converted.mp3", "wb") as f:
    for chunk in audio_stream:
        f.write(chunk)

Voice Settings Override

Fine-tune the target voice for a single request without changing its stored defaults:

python

from elevenlabs import VoiceSettings

audio_stream = client.speech_to_speech.convert(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    audio=audio_file,
    model_id="eleven_multilingual_sts_v2",
    voice_settings=VoiceSettings(
        stability=0.5,
        similarity_boost=0.75,
        style=0.0,
        use_speaker_boost=True,
    ),
)

Stability: lower = more emotional range (follows the source more freely), higher = steadier delivery.
Similarity boost: higher = closer to the target voice's timbre, may amplify source artifacts.
Style: exaggerates the target voice's unique characteristics (v2+ models).
Speaker boost: post-processing to sharpen clarity of the target voice.

Cleaning Up Noisy Source Audio

If the input recording is noisy, either pre-process with the voice-isolator skill or pass

remove_background_noise=True

to do it in a single call:

python

audio_stream = client.speech_to_speech.convert(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    audio=audio_file,
    model_id="eleven_multilingual_sts_v2",
    remove_background_noise=True,
)

Cleaner input almost always produces better conversion — the model is trying to match phonemes and prosody, and background noise gets in the way.

Low-Latency PCM Input

If you already have raw 16-bit PCM mono @ 16kHz, passing

file_format="pcm_s16le_16"

skips decoding and reduces latency:

python

audio_stream = client.speech_to_speech.convert(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    audio=pcm_bytes,
    model_id="eleven_multilingual_sts_v2",
    file_format="pcm_s16le_16",
)

Pair this with

optimize_streaming_latency

(0–4) as a query param for further latency reductions at some quality cost.

Output Formats

Format	Description
`mp3_44100_128`	MP3 44.1kHz 128kbps (default) — good for web/apps
`mp3_44100_192`	MP3 44.1kHz 192kbps (Creator+) — higher quality
`mp3_44100_64`	MP3 44.1kHz 64kbps — smaller files
`mp3_22050_32`	MP3 22.05kHz 32kbps — smallest MP3
`pcm_16000`	Raw PCM 16kHz — real-time pipelines
`pcm_24000`	Raw PCM 24kHz — good streaming balance
`pcm_44100`	Raw PCM 44.1kHz (Pro+) — CD quality
`pcm_48000`	Raw PCM 48kHz (Pro+) — highest quality
`ulaw_8000`	μ-law 8kHz — Twilio / telephony
`alaw_8000`	A-law 8kHz — telephony
`opus_48000_64`	Opus 48kHz 64kbps — efficient streaming

Deterministic Output

Pass a

seed

to make repeated conversions of the same input return (best-effort) identical audio — useful for testing and A/B comparisons.

python

audio_stream = client.speech_to_speech.convert(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    audio=audio_file,
    model_id="eleven_multilingual_sts_v2",
    seed=12345,
)

Input Audio Best Practices

The conversion quality is bounded by the input recording — the model can only swap the timbre, not rescue a bad source. A few practical rules:

Be expressive. Whisper, shout, laugh, cry — the model preserves all of it. Flat input gives you flat output.
Watch microphone gain. Too quiet and the model under-detects phonemes; too loud and clipping bleeds into the conversion. Aim for healthy peaks, no clipping.
Accent and cadence transfer from the source, not the target. If you read in an American accent and target the British "George" voice, you get George's timbre with an American accent. To dub into a different accent or language, record someone speaking in that target accent/language and convert into a cloned/library voice.
Clean up noise first. Either pass
```
remove_background_noise=True
```
or run the source through the voice-isolator skill before conversion. Noise hurts more here than in TTS.
Split long recordings. Anything over 5 minutes must be chunked. Cut at natural pauses, convert each piece, and concatenate the resulting audio.

Common Workflows

Re-voice a narration — keep the performance of a scratch recording, swap in a different narrator voice.
Localize / dub — convert a voice-over into the same speaker's cloned voice in another language (using
```
eleven_multilingual_sts_v2
```
).
Create character voices — act out a line yourself, convert into a distinctive character voice for games or animation.
Anonymize a speaker — replace a recognizable voice with a neutral pre-made voice while preserving what was said and how.
Pair with voice-isolator — isolate the source voice first (or set
```
remove_background_noise=True
```
) for noisy field recordings before conversion.
Pair with voice cloning — clone a target voice from a short sample, then use its
```
voice_id
```
here as the conversion target.

Error Handling

python

try:
    audio_stream = client.speech_to_speech.convert(
        voice_id="JBFqnCBsd6RMkjVDRZzb",
        audio=audio_file,
        model_id="eleven_multilingual_sts_v2",
    )
except Exception as e:
    print(f"Voice changer failed: {e}")

Common errors:

401: Invalid API key
422: Invalid parameters (check
```
voice_id
```
,
```
model_id
```
, or
```
file_format
```
vs the supplied audio)
429: Rate limit exceeded

References

Installation Guide

voice-changer

NPX Install

Tags

SKILL.md Content

ElevenLabs Voice Changer

Key Facts

Quick Start

Python

JavaScript

cURL

Parameters

Models

Languages (
`eleven_multilingual_sts_v2`
)

Target Voices

Converting from a URL

Voice Settings Override

Cleaning Up Noisy Source Audio

Low-Latency PCM Input

Output Formats

Deterministic Output

Input Audio Best Practices

Common Workflows

Error Handling

References

voice-changer

NPX Install

Tags

SKILL.md Content

ElevenLabs Voice Changer

Key Facts

Quick Start

Python

JavaScript

cURL

Parameters

Models

Languages (eleven_multilingual_sts_v2)

Target Voices

Converting from a URL

Voice Settings Override

Cleaning Up Noisy Source Audio

Low-Latency PCM Input

Output Formats

Deterministic Output

Input Audio Best Practices

Common Workflows

Error Handling

References

Languages (
`eleven_multilingual_sts_v2`
)