| name | voice-isolator |
| description | Remove background noise and isolate vocals/speech from audio using ElevenLabs Voice Isolator (audio isolation) API. Use when cleaning up noisy recordings, removing music or background ambience from dialogue, isolating speech from field recordings, preparing audio for transcription, extracting vocals, or any "denoise / clean up / isolate voice" task. |
| license | MIT |
| compatibility | Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY). |
| metadata | {"openclaw":{"requires":{"env":["ELEVENLABS_API_KEY"]},"primaryEnv":"ELEVENLABS_API_KEY"}} |
ElevenLabs Voice Isolator
Removes background noise from audio and isolates vocals/speech — useful for cleaning up noisy recordings, prepping audio for transcription, or pulling dialogue out of a mixed track.
Setup: See Installation Guide. For JavaScript, use @elevenlabs/* packages only.
Quick Start
Python
from elevenlabs import ElevenLabs
client = ElevenLabs()
with open("noisy.mp3", "rb") as audio_file:
audio_stream = client.audio_isolation.convert(audio=audio_file)
with open("clean.mp3", "wb") as f:
for chunk in audio_stream:
f.write(chunk)
JavaScript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createReadStream, createWriteStream } from "fs";
const client = new ElevenLabsClient();
const audioStream = await client.audioIsolation.convert({
audio: createReadStream("noisy.mp3"),
});
audioStream.pipe(createWriteStream("clean.mp3"));
cURL
curl -X POST "https://api.elevenlabs.io/v1/audio-isolation" \
-H "xi-api-key: $ELEVENLABS_API_KEY" \
-F "audio=@noisy.mp3" \
--output clean.mp3
Parameters
| Parameter | Type | Default | Description |
|---|
audio | file (required) | — | Audio file with vocals/speech to isolate |
file_format | string | other | other for any encoded audio, or pcm_s16le_16 for 16-bit PCM mono @ 16kHz little-endian (lower latency) |
Isolating from a URL
import requests
from io import BytesIO
from elevenlabs import ElevenLabs
client = ElevenLabs()
audio_url = "https://example.com/noisy.mp3"
response = requests.get(audio_url)
audio_data = BytesIO(response.content)
audio_stream = client.audio_isolation.convert(audio=audio_data)
with open("clean.mp3", "wb") as f:
for chunk in audio_stream:
f.write(chunk)
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:
audio_stream = client.audio_isolation.convert(
audio=pcm_bytes,
file_format="pcm_s16le_16",
)
Supported Formats
Any common encoded audio/video container works as input (MP3, WAV, M4A, FLAC, OGG, WebM, MP4, etc.). Response is a streamed MP3 by default.
Common Workflows
- Clean up interview/podcast recordings — strip room tone, HVAC, traffic before editing.
- Prep noisy audio for Speech-to-Text — isolate voice first, then pass through
speech_to_text.convert() for better transcription accuracy.
- Extract dialogue from mixed tracks — pull vocals out of a track with music/SFX.
- Pre-processing for Voice Changer — isolate the source voice before applying voice transformation.
Error Handling
try:
audio_stream = client.audio_isolation.convert(audio=audio_file)
except Exception as e:
print(f"Voice isolation failed: {e}")
Common errors:
- 401: Invalid API key
- 422: Invalid parameters (e.g. wrong
file_format for the supplied audio)
- 429: Rate limit exceeded
References