elevenlabs

Files (2)

• SKILL.md
• reference.md

SKILL.md (first lines)

# ElevenLabs Audio Generation

Requires `ELEVENLABS_API_KEY` in `.env`.

## Text-to-Speech

```python
from elevenlabs.client import ElevenLabs
from elevenlabs import save, VoiceSettings
import os

client = ElevenLabs(api_key=os.getenv("ELEVENLABS_API_KEY"))

audio = client.text_to_speech.convert(
    text="Welcome to my video!",
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    model_id="eleven_multilingual_v2",
    voice_settings=VoiceSettings(
        stability=0.5,
        similarity_boost=0.75,
        style=0.5,
        speed=1.0
    )
)
save(audio, "voiceover.mp3")
```

### Models

| Model | Quality | SSML Support | Notes |
|-------|---------|--------------|-------|
| `eleven_multilingual_v2` | Highest consistency | None | Stable, production-ready, 29 languages |
| `eleven_flash_v2_5` | Good | `<break>`, `<phoneme>` | Fast, supports pause/pronunciation tags |
| `eleven_turbo_v2_5` | Good | `<break>`, `<phoneme>` | Fastest latency |
| `eleven_v3` | Most expressive | None | Alpha — unreliable, needs prompt engineering |

**Choose:** multilingual_v2 for reliability, flash/turbo for SSML control, v3 for maximum expressiveness (expect retakes).

### Voice Settings by Style

| Style | stability | similarity | style | speed |
|-------|-----------|------------|-------|-------|
| Natural/professional | 0.75-0.85 | 0.9 | 0.0-0.1 | 1.0 |
| Conversational | 0.5-0.6 | 0.85 | 0.3-0.4 | 0.9-1.0 |
| Energetic/YouTuber | 0.3-0.5 | 0.75 | 0.5-0.7 | 1.0-1.1 |

### Pauses Between Sections

**With flash/turbo models:** Use SSML break tags inline:
```
...end of section. <break time="1.5s" /> Start of next...
```
Max 3 seconds per break. Excessive breaks can cause speed artifacts.

**With multilingual_v2 / v3:** No SSML support. Options:
- Paragraph breaks (blank lines) — creates ~0.3-0.5s natural pause
- Post-process with ffmpeg: split audio and insert silence

**WARNING:** `...` (ellipsis) is NOT a reliable pause — it can be vocalized as a word/sound. Do not use ellipsis as a pause mechanism.

### Pronunciation Control

**Phonetic spelling (any model):** Write words as you want them pronounced:
- `Janus` → `Jan-us`
- `nginx` → `engine-x`
- Use dashes, capitals, apostrophes to guide pronunciation

**SSML phoneme tags (flash/turbo only):**
```
<phoneme alphabet="ipa" ph="ˈdʒeɪnəs">Janus</phoneme>
```

### Iterative Workflow

1. Generate → listen → identify pronunciation/pacing issues
2. Adjust: phonetic spellings, break tags, voice settings
3. Regenerate. If pauses aren't precise enough, add silence in post with ffmpeg rather than fighting the TTS engine.

## Voice Cloning

### Instant Voice Clone

```python
with open("sample.mp3", "rb") as f:
    voice = client.voices.ivc.create(
        name="My Voice",
        files=[f],
        remove_background_noise=True
    )
print(f"Voice ID: {voice.voice_id}")
```

- Use `client.voices.ivc.create()` (not `client.voices.clone()`)
- Pass file handles in binary mode (`"rb"`), not paths
- Convert m4a first: `ffmpeg -i input.m4a -codec:a libmp3lame -qscale:a 2 output.mp3`
- Multiple samples (2-3 clips) improve accuracy
- Save voice ID for reuse

**Professional Voice Clone:** Requires Creator plan+, 30+ min audio. See [reference.md](reference.md).

## Sound Effects

Max 22 seconds per generation.

```python
result = client.text_to_sound_effects.convert(
    text="Thunder rumbling followed by heavy rain",
    duration_seconds=10,
    prompt_influence=0.3
)
with open("thunder.mp3", "wb") as f:
    for chunk in result:
        f.write(chunk)
```

**Prompt tips:** Be specific — "Heavy footsteps on wooden floorboards, slow and deliberate, with creaking"

## Music Generation

From xaralis/video-toolkit, MIT.

More from xaralis/video-toolkit