text-to-speech

Files (4)

• SKILL.md
• installation.md · references/
• streaming.md · references/
• voice-settings.md · references/

SKILL.md (first lines)

# ElevenLabs Text-to-Speech

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

> **Setup:** See [Installation Guide](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)

From Harmeet10000/skills, MIT.

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