Agent Skills

text-to-speech

videoelevenlabs12K installs

Convert text to speech using ElevenLabs voice AI. Use when generating audio from text, creating voiceovers, building voice apps, or synthesizing speech in 70+ languages.

Install

npx skills add https://github.com/elevenlabs/skills --skill text-to-speech
SKILL.md

ElevenLabs Text-to-Speech

Generate natural speech from text - supports 90+ languages, multiple models for quality vs latency tradeoffs.

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

Quick Start

Python

from elevenlabs import ElevenLabs

client = ElevenLabs()

audio = client.text_to_speech.convert(
    text="Hello, welcome to ElevenLabs!",
    voice_id="JBFqnCBsd6RMkjVDRZzb",  # George
    model_id="eleven_multilingual_v2"
)

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

JavaScript

import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createWriteStream } from "fs";
import { Readable } from "stream";

const client = new ElevenLabsClient();
const audio = await client.textToSpeech.convert("JBFqnCBsd6RMkjVDRZzb", {
  text: "Hello, welcome to ElevenLabs!",
  modelId: "eleven_multilingual_v2",
});
// convert() returns a web ReadableStream — bridge it to a Node stream to write to disk
Readable.fromWeb(audio).pipe(createWriteStream("output.mp3"));

CLI

Use say to play text immediately with the default voice and eleven_v3 model:

elevenlabs say "Hello!"

Pipe text into say when another command produces the input:

echo "The build finished successfully." | elevenlabs say

Use the API command when you need to set request parameters directly:

elevenlabs text-to-speech convert --voice-id JBFqnCBsd6RMkjVDRZzb \
  --text "Hello!" --model-id eleven_multilingual_v2 --output output.mp3

The CLI reads ELEVENLABS_API_KEY from the environment automatically.

Models

Model ID Languages Latency Best For
eleven_v4 90+ Standard Highest quality, expressive content and dialogue
eleven_v4_turbo 90+ ~100ms Expressive real-time dialogue through the Text to Dialogue WebSocket
eleven_v3 70+ Standard Highest quality, emotional range
eleven_multilingual_v2 29 Standard High quality, long-form content
eleven_flash_v2_5 32 ~75ms Ultra-low latency, real-time
eleven_flash_v2 English ~75ms English-only, fastest
eleven_turbo_v2_5 32 ~250-300ms Balanced quality/speed
eleven_turbo_v2 English ~250-300ms English-only, balanced

Voice IDs

Use pre-made voices or create custom voices in the dashboard.

Popular voices:

  • JBFqnCBsd6RMkjVDRZzb - George (male, narrative)
  • EXAVITQu4vr4xnSDxMaL - Sarah (female, soft)
  • onwK4e9ZLuTAKqWW03F9 - Daniel (male, authoritative)
  • XB0fDUnXU5powFXDhCwa - Charlotte (female, conversational)
voices = client.voices.get_all()
for voice in voices.voices:
    print(f"{voice.voice_id}: {voice.name}")

Voice Settings

Fine-tune how the voice sounds:

  • Stability: How consistent the voice stays. Lower values = more emotional range and variation, but can sound unstable. Higher = steady, predictable delivery.
  • Similarity boost: How closely to match the original voice sample. Higher values sound more like the original but may amplify audio artifacts.
  • Style: Exaggerates the voice's unique style characteristics. It is not available for Eleven v4 models.
  • Speed: Adjusts speech rate on supported models. It is not available for Eleven v4 models.
  • Speaker boost: Post-processing that enhances clarity and voice similarity.
from elevenlabs import VoiceSettings

audio = client.text_to_speech.convert(
    text="Customize my voice settings.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    voice_settings=VoiceSettings(
        stability=0.5,
        similarity_boost=0.75,
        style=0.5,
        speed=1.0,             # 0.25 to 4.0 (default 1.0)
        use_speaker_boost=True
    )
)

Language Selection

Use language_code with models that support language enforcement to guide pronunciation and text normalization. Unsupported language codes are ignored, and language_code is not supported on eleven_multilingual_v2.

audio = client.text_to_speech.convert(
    text="Bonjour, comment allez-vous?",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_v3",
    language_code="fr"  # ISO 639-1 code
)

Text Normalization

Controls how numbers, dates, and abbreviations are converted to spoken words. For example, "01/15/2026" becomes "January fifteenth, twenty twenty-six":

  • "auto" (default): Model decides based on context
  • "on": Always normalize (use when you want natural speech)
  • "off": Speak literally (use when you want "zero one slash one five...")
audio = client.text_to_speech.convert(
    text="Call 1-800-555-0123 on 01/15/2026",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    apply_text_normalization="on"
)

Request Stitching

When generating long audio in multiple requests, the audio can have pops, unnatural pauses, or tone shifts at the boundaries. Request stitching solves this by letting each request know what comes before/after it:

# First request
audio1 = client.text_to_speech.convert(
    text="This is the first part.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    next_text="And this continues the story."
)

# Second request using previous context
audio2 = client.text_to_speech.convert(
    text="And this continues the story.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    previous_text="This is the first part."
)

Output Formats

Format Description
mp3_44100_128 MP3 44.1kHz 128kbps (default) - compressed, good for web/apps
mp3_44100_192 MP3 44.1kHz 192kbps (Creator+) - higher quality compressed
mp3_44100_64 MP3 44.1kHz 64kbps - lower quality, smaller files
mp3_22050_32 MP3 22.05kHz 32kbps - smallest MP3 files
pcm_16000 Raw PCM 16kHz - use for real-time processing
pcm_22050 Raw PCM 22.05kHz
pcm_24000 Raw PCM 24kHz - good balance for streaming
pcm_44100 Raw PCM 44.1kHz (Pro+) - CD quality
pcm_48000 Raw PCM 48kHz (Pro+) - highest quality
ulaw_8000 μ-law 8kHz - standard for phone systems (Twilio, telephony)
alaw_8000 A-law 8kHz - telephony (alternative to μ-law)
opus_48000_64 Opus 48kHz 64kbps - efficient streaming codec
wav_44100 WAV 44.1kHz - uncompressed with headers

Streaming

For real-time applications, use the stream method (returns audio chunks as they're generated):

audio_stream = client.text_to_speech.stream(
    text="This text will be streamed as audio.",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_flash_v2_5"  # Ultra-low latency
)

for chunk in audio_stream:
    play_audio(chunk)

See references/streaming.md for WebSocket streaming.

Error Handling

try:
    audio = client.text_to_speech.convert(
        text="Generate speech",
        voice_id="invalid-voice-id"
    )
except Exception as e:
    print(f"API error: {e}")

Common errors:

  • 401: Invalid API key
  • 422: Invalid parameters (check voice_id, model_id)
  • 429: Rate limit exceeded

Tracking Costs

Monitor character usage via response headers (x-character-count, request-id):

response = client.text_to_speech.convert.with_raw_response(
    text="Hello!", voice_id="JBFqnCBsd6RMkjVDRZzb", model_id="eleven_multilingual_v2"
)
audio = response.parse()
print(f"Characters used: {response.headers.get('x-character-count')}")

References

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