npx skills add ...
npx skills add elevenlabs/skills --skill voice-isolator
npx skills add elevenlabs/skills --skill voice-isolator
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.
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.
| 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) |
If you already have raw 16-bit PCM mono @ 16kHz, passing file_format="pcm_s16le_16" skips decoding and reduces latency:
Any common encoded audio/video container works as input (MP3, WAV, M4A, FLAC, OGG, WebM, MP4, etc.). Response is a streamed MP3 by default.
speech_to_text.convert() for better transcription accuracy.Common errors:
file_format for the supplied audio)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 -X POST "https://api.elevenlabs.io/v1/audio-isolation" \
-H "xi-api-key: $ELEVENLABS_API_KEY" \
-F "audio=@noisy.mp3" \
--output clean.mp3import 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)audio_stream = client.audio_isolation.convert(
audio=pcm_bytes,
file_format="pcm_s16le_16",
)try:
audio_stream = client.audio_isolation.convert(audio=audio_file)
except Exception as e:
print(f"Voice isolation failed: {e}")