> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/yocxy2/chatterboxyocxy/llms.txt
> Use this file to discover all available pages before exploring further.

# Chatterbox-Multilingual

> Zero-shot voice cloning across 23+ languages for global applications

## Overview

Chatterbox-Multilingual extends the capabilities of the base Chatterbox model to support 23+ languages, making it ideal for global applications and localization projects. With 500M parameters, it maintains high-quality voice cloning while providing multilingual support.

<CardGroup cols={2}>
  <Card title="23+ Languages" icon="globe">
    Support for major world languages including European, Asian, and Middle Eastern languages.
  </Card>

  <Card title="Zero-Shot Cloning" icon="microphone">
    Clone voices across languages without fine-tuning or training.
  </Card>

  <Card title="CFG Control" icon="sliders">
    Same advanced controls as the base model for fine-tuning output.
  </Card>

  <Card title="Cross-Language" icon="language">
    Transfer voices across different languages while preserving characteristics.
  </Card>
</CardGroup>

## Model Specifications

* **Model Size**: 500M parameters
* **Languages**: 23+ supported languages
* **Sample Rate**: 24,000 Hz
* **Architecture**: T3 transformer (multilingual config) + S3Gen decoder
* **Repository**: `ResembleAI/chatterbox`

## Supported Languages

The multilingual model supports the following 23 languages:

<AccordionGroup>
  <Accordion title="European Languages">
    * **Danish** (da)
    * **German** (de)
    * **Greek** (el)
    * **English** (en)
    * **Spanish** (es)
    * **Finnish** (fi)
    * **French** (fr)
    * **Italian** (it)
    * **Dutch** (nl)
    * **Norwegian** (no)
    * **Polish** (pl)
    * **Portuguese** (pt)
    * **Russian** (ru)
    * **Swedish** (sv)
  </Accordion>

  <Accordion title="Asian Languages">
    * **Chinese** (zh)
    * **Japanese** (ja)
    * **Korean** (ko)
    * **Hindi** (hi)
    * **Malay** (ms)
  </Accordion>

  <Accordion title="Middle Eastern & African Languages">
    * **Arabic** (ar)
    * **Hebrew** (he)
    * **Turkish** (tr)
    * **Swahili** (sw)
  </Accordion>
</AccordionGroup>

## Hardware Requirements

<CardGroup cols={2}>
  <Card title="Minimum (CPU)" icon="microchip">
    * 6GB RAM
    * CPU inference supported
    * Slower generation times
  </Card>

  <Card title="Recommended (GPU)" icon="server">
    * NVIDIA GPU with 6GB+ VRAM
    * CUDA support
    * Near real-time generation
  </Card>
</CardGroup>

<Note>
  The model also supports Apple Silicon (MPS) for Mac users with M1/M2/M3 chips.
</Note>

## Usage

### Basic Generation

```python theme={null}
import torchaudio as ta
from chatterbox.mtl_tts import ChatterboxMultilingualTTS

# Load the multilingual model
model = ChatterboxMultilingualTTS.from_pretrained(device="cuda")

# Generate French speech
french_text = "Bonjour, comment ça va? Ceci est le modèle de synthèse vocale multilingue Chatterbox, il prend en charge 23 langues."
wav = model.generate(french_text, language_id="fr")

ta.save("test-french.wav", wav, model.sr)
```

### Multiple Languages

```python theme={null}
import torchaudio as ta
from chatterbox.mtl_tts import ChatterboxMultilingualTTS

model = ChatterboxMultilingualTTS.from_pretrained(device="cuda")

# Spanish
spanish_text = "Hola, ¿cómo estás? Este es un ejemplo de síntesis de voz en español."
wav_spanish = model.generate(spanish_text, language_id="es")
ta.save("test-spanish.wav", wav_spanish, model.sr)

# Chinese
chinese_text = "你好，今天天气真不错，希望你有一个愉快的周末。"
wav_chinese = model.generate(chinese_text, language_id="zh")
ta.save("test-chinese.wav", wav_chinese, model.sr)

# German
german_text = "Guten Tag, wie geht es Ihnen? Dies ist ein Test der deutschen Sprachsynthese."
wav_german = model.generate(german_text, language_id="de")
ta.save("test-german.wav", wav_german, model.sr)
```

### Voice Cloning Across Languages

```python theme={null}
import torchaudio as ta
from chatterbox.mtl_tts import ChatterboxMultilingualTTS

model = ChatterboxMultilingualTTS.from_pretrained(device="cuda")

# Clone a voice and use it for different languages
reference_audio = "english_speaker.wav"

# Generate in French with English speaker's voice
french_text = "Bonjour, je parle français maintenant."
wav = model.generate(
    french_text,
    language_id="fr",
    audio_prompt_path=reference_audio
)

ta.save("french-with-english-voice.wav", wav, model.sr)
```

<Warning>
  When using cross-language voice cloning, ensure the reference clip matches the target language, or set `cfg_weight=0` to avoid accent transfer.
</Warning>

### Getting Supported Languages

```python theme={null}
from chatterbox.mtl_tts import ChatterboxMultilingualTTS

# Get dictionary of all supported languages
languages = ChatterboxMultilingualTTS.get_supported_languages()

for code, name in languages.items():
    print(f"{code}: {name}")
```

## Generation Parameters

| Parameter            | Default  | Description                                       |
| -------------------- | -------- | ------------------------------------------------- |
| `language_id`        | Required | Two-letter language code (e.g., "fr", "es", "zh") |
| `temperature`        | 0.8      | Controls randomness in token selection            |
| `top_p`              | 1.0      | Nucleus sampling threshold                        |
| `min_p`              | 0.05     | Minimum probability threshold                     |
| `repetition_penalty` | 2.0      | Penalizes repeated tokens                         |
| `cfg_weight`         | 0.5      | Classifier-free guidance strength                 |
| `exaggeration`       | 0.5      | Emotional intensity level                         |
| `audio_prompt_path`  | None     | Path to reference audio for voice cloning         |

<Note>
  The `language_id` parameter is required for the multilingual model. Use the two-letter ISO 639-1 language codes.
</Note>

## Best Practices

### Language-Specific Tips

<Accordion title="Chinese (zh)">
  The model handles Chinese characters and punctuation. Use appropriate Chinese punctuation marks like 。？！for best results.
</Accordion>

<Accordion title="Japanese (ja)">
  Both Hiragana, Katakana, and Kanji are supported. The model automatically handles mixed scripts.
</Accordion>

<Accordion title="Arabic (ar)">
  Right-to-left text is properly handled. Ensure your text includes appropriate diacritical marks for best pronunciation.
</Accordion>

<Accordion title="European Languages">
  The model handles accented characters (é, ñ, ü, etc.) naturally. Include proper accents for accurate pronunciation.
</Accordion>

### Cross-Language Voice Cloning

1. **Matching Languages**: For best results, use a reference clip in the same language as your target text
2. **Accent Transfer**: If accent transfer occurs with cross-language cloning, set `cfg_weight=0`
3. **Reference Quality**: Use clear, noise-free reference audio for consistent results
4. **Default Settings**: The default parameters (`exaggeration=0.5`, `cfg_weight=0.5`) work well across all languages

<Tip>
  For cross-language applications where you need to maintain voice consistency across multiple languages, start with a high-quality reference clip and test with `cfg_weight` values between 0.3 and 0.5.
</Tip>

## Performance Characteristics

<CardGroup cols={2}>
  <Card title="Generation Speed" icon="clock">
    Similar to base Chatterbox model with 10-step decoding. Speed varies slightly by language complexity.
  </Card>

  <Card title="Audio Quality" icon="star">
    High-fidelity 24kHz output across all supported languages with natural prosody and intonation.
  </Card>
</CardGroup>

## Built-in Watermarking

Every audio file generated by Chatterbox-Multilingual includes Resemble AI's Perth (Perceptual Threshold) watermark - imperceptible neural watermarks that survive MP3 compression, audio editing, and common manipulations.

```python theme={null}
import perth
import librosa

# Load the watermarked audio
watermarked_audio, sr = librosa.load("output.wav", sr=None)

# Initialize watermarker
watermarker = perth.PerthImplicitWatermarker()

# Extract watermark
watermark = watermarker.get_watermark(watermarked_audio, sample_rate=sr)
print(f"Extracted watermark: {watermark}")  # 0.0 or 1.0
```

## Use Cases

* **Global Applications**: Build TTS systems for international audiences
* **Localization**: Create localized content in multiple languages
* **Language Learning**: Generate pronunciation examples in various languages
* **Multilingual Voice Agents**: Conversational AI that speaks multiple languages
* **Content Translation**: Convert written content to speech across languages
* **Accessibility**: Text-to-speech for global accessibility features

## Language Support Details

The model includes comprehensive language support with proper handling of:

* Language-specific punctuation
* Diacritical marks and accents
* Script systems (Latin, Cyrillic, Arabic, Chinese, Japanese, Korean)
* Language-appropriate prosody and intonation
* Cultural speech patterns

## Comparison with Other Models

| Feature      | Chatterbox       | Chatterbox-Turbo | Chatterbox-Multilingual |
| ------------ | ---------------- | ---------------- | ----------------------- |
| Parameters   | 500M             | 350M             | 500M                    |
| Languages    | English          | English          | 23+                     |
| CFG Control  | Yes              | No               | Yes                     |
| Exaggeration | Yes              | No               | Yes                     |
| Speed        | Medium           | Fast             | Medium                  |
| Best For     | Creative control | Low latency      | Multi-language          |

## Next Steps

<CardGroup cols={2}>
  <Card title="Installation" icon="download" href="/quickstart">
    Install Chatterbox and get started
  </Card>

  <Card title="API Reference" icon="code" href="/api/chatterbox-multilingual-tts">
    Explore all parameters and methods
  </Card>
</CardGroup>