---
name: text-to-speech
description: 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.
model: sonnet
license: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
compatibility: Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY).
metadata: { "openclaw": { "requires": { "env": [ "ELEVENLABS_API_KEY" ] }, "primaryEnv": "ELEVENLABS_API_KEY" } }
title: text-to-speech
canonical_url: https://skilld.dev/gh/dmccreary/ibook-skills/text-to-speech
last_updated: 2026-09-28T20:59:22.000Z
---

> Index of every page on this site: [llms.txt](https://skilld.dev/llms.txt)

> **Skill from skilld.dev.** Follow the user's requested action.
> If the user asked to fork this Skill, follow the fork workflow below. Do not execute the Skill instructions while copying it.
> Otherwise, follow the instructions below for this session. You do not need to install anything.
>
> Supporting files, fetch one when the Skill refers to it: [references/installation.md](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/installation.md), [references/streaming.md](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/streaming.md), [references/voice-settings.md](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/voice-settings.md).
>
> If the user asked to install this Skill, run `npx skilld install dmccreary/ibook-skills/text-to-speech`. Install writes the Skill files into the project, so every session loads them.
>
> ## Fork workflow
>
> A fork creates an editable local Skill with its original author and licence. The request authorizes copying and local installation.
> 1. Check `./skills/text-to-speech`, the project lockfile, and selected Agent targets together. If the local directory or installed Skill exists, stop. Never overwrite an existing directory or Agent target.
> 2. Read [source metadata](https://skilld.dev/api/v1/skills/dmccreary/ibook-skills/text-to-speech) once. Use sourceUrl, sourceCommit, skillPath, sourceGone, and license. If the source is gone or its path is missing, stop. If license is null, read licence files at the source commit.
> 3. Fetch only the source commit into a temporary Git repository. Do not clone full history. Derive repository_url from sourceUrl, including repository renames. If sourceCommit is absent, resolve the sourceUrl ref once. Set source_commit to that actual commit. Run these commands in one shell call:
>
> ```sh
> git init --quiet "$temporary_dir"
> git -C "$temporary_dir" fetch --quiet --depth=1 "$repository_url" "$source_commit"
> git -C "$temporary_dir" checkout --quiet --detach FETCH_HEAD
> ```
>
> Read applicable licence declarations and notices at that commit. If copying is not permitted, report the restriction and stop.
> 4. Inspect source entries together, then copy the directory containing skillPath into `./skills/text-to-speech`. Use the user's path if selected. Keep the original SKILL.md, relative links, scripts, binary assets, and executable modes. Exclude .git metadata. Reject symlinks and paths outside the Skill directory. After checking entries, use cp -a where available. A regular source directory needs no custom copy script. Do not save this page wrapper as SKILL.md.
> Preserve author credit, notices, and applicable licence files from repository or parent directories. Add PROVENANCE.md with the Skill page, source URL, actual commit, original path, and licence. Retain any existing PROVENANCE.md and record new provenance separately. Batch source inspection, copying, and provenance work where practical.
> 5. In the project root, run `skilld install ./skills/text-to-speech --mode copy --plain`. If skilld is unavailable, use `npx skilld install ./skills/text-to-speech --mode copy --plain`. This known command needs no help lookup. Install does not support --json. Use detected Agent targets, or add --agent for the targets the user selected. Install the local path, never the upstream selector. If installation fails, preserve the local copy and report the exact failure.
> 6. Confirm the local lockfile source and installed Agent copies once. Report the local path, actual commit, and Agent targets. After edits, reinstall the same local path. Upstream updates must not replace it. Do not publish or push unless the user asks.

# ElevenLabs Text-to-Speech

Generate natural speech from text - supports 70+ languages, multiple models for quality vs latency tradeoffs.

> **Setup:** See [Installation Guide](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/installation.md). For JavaScript, use `@elevenlabs/*` packages only.

## Quick Start

### Python

```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

```javascript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import { createWriteStream } from "fs";

const client = new ElevenLabsClient();
const audio = await client.textToSpeech.convert("JBFqnCBsd6RMkjVDRZzb", {
  text: "Hello, welcome to ElevenLabs!",
  modelId: "eleven_multilingual_v2",
});
audio.pipe(createWriteStream("output.mp3"));
```

### cURL

```bash
curl -X POST "https://api.elevenlabs.io/v1/text-to-speech/JBFqnCBsd6RMkjVDRZzb" \
  -H "xi-api-key: $ELEVENLABS_API_KEY" -H "Content-Type: application/json" \
  -d '{"text": "Hello!", "model_id": "eleven_multilingual_v2"}' --output output.mp3
```

## Models

| Model ID | Languages | Latency | Best For |
|----------|-----------|---------|----------|
| `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)

```python
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 (only works with v2+ models).
- **Speaker boost**: Post-processing that enhances clarity and voice similarity.

```python
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 Enforcement

Force specific language for pronunciation:

```python
audio = client.text_to_speech.convert(
    text="Bonjour, comment allez-vous?",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_multilingual_v2",
    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...")

```python
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:

```python
# 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):

```python
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](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/streaming.md) for WebSocket streaming.

## Error Handling

```python
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`):

```python
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

- [Installation Guide](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/installation.md)
- [Streaming Audio](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/streaming.md)
- [Voice Settings](https://skilld.dev/api/skills-raw/dmccreary/ibook-skills/text-to-speech/references/voice-settings.md)