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Chatterbox Multilingual enables you to generate natural speech in 23+ languages with zero-shot voice cloning. The model supports cross-lingual synthesis, allowing you to use a voice from one language and generate speech in another.

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Supported Languages

Chatterbox Multilingual supports the following 23 languages:
LanguageCodeLanguageCode
ArabicarKoreanko
ChinesezhMalayms
DanishdaDutchnl
EnglishenNorwegianno
FinnishfiPolishpl
FrenchfrPortuguesept
GermandeRussianru
GreekelSpanishes
HebrewheSwedishsv
HindihiSwahilisw
ItalianitTurkishtr
Japaneseja
You can programmatically access the supported languages using:
from chatterbox.mtl_tts import ChatterboxMultilingualTTS
languages = ChatterboxMultilingualTTS.get_supported_languages()
print(languages)  # {'ar': 'Arabic', 'da': 'Danish', ...}

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Using the language_id Parameter

The language_id parameter specifies which language to generate. It’s required for the multilingual model.

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Basic Usage

import torchaudio as ta
from chatterbox.mtl_tts import ChatterboxMultilingualTTS

# Initialize 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."
wav = model.generate(french_text, language_id="fr")
ta.save("french_output.wav", wav, model.sr)

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

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Language Code Format

Use the two-letter ISO language codes (case-insensitive): 
# Both work - the model converts to lowercase internally
wav = model.generate(text, language_id="fr")  # Lowercase
wav = model.generate(text, language_id="FR")  # Uppercase (converted internally)

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Validation

The model validates the language_id and raises an error for unsupported languages: 
try:
    wav = model.generate("Hello", language_id="xx")  # Invalid code
except ValueError as e:
    print(e)  # "Unsupported language_id 'xx'. Supported languages: ar, da, de..."

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Examples in Multiple Languages

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European Languages

from chatterbox.mtl_tts import ChatterboxMultilingualTTS
import torchaudio as ta

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

# Spanish
spanish = "Hola, ¿cómo estás? Este es un ejemplo en español."
wav = model.generate(spanish, language_id="es")
ta.save("spanish.wav", wav, model.sr)

# German
german = "Guten Tag, wie geht es Ihnen heute?"
wav = model.generate(german, language_id="de")
ta.save("german.wav", wav, model.sr)

# Italian
italian = "Buongiorno, come stai oggi?"
wav = model.generate(italian, language_id="it")
ta.save("italian.wav", wav, model.sr)

# French (from example_tts.py)
french = "Bonjour, comment ça va? Ceci est le modèle de synthèse vocale multilingue Chatterbox, il prend en charge 23 langues."
wav = model.generate(french, language_id="fr")
ta.save("french.wav", wav, model.sr)

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Asian Languages

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

# Japanese
japanese = "こんにちは、お元気ですか？"
wav = model.generate(japanese, language_id="ja")
ta.save("japanese.wav", wav, model.sr)

# Korean
korean = "안녕하세요, 오늘 날씨가 참 좋네요."
wav = model.generate(korean, language_id="ko")
ta.save("korean.wav", wav, model.sr)

# Hindi
hindi = "नमस्ते, आप कैसे हैं?"
wav = model.generate(hindi, language_id="hi")
ta.save("hindi.wav", wav, model.sr)

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Other Languages

# Arabic
arabic = "مرحبا، كيف حالك اليوم؟"
wav = model.generate(arabic, language_id="ar")
ta.save("arabic.wav", wav, model.sr)

# Hebrew
hebrew = "שלום, מה שלומך?"
wav = model.generate(hebrew, language_id="he")
ta.save("hebrew.wav", wav, model.sr)

# Russian
russian = "Здравствуйте, как дела?"
wav = model.generate(russian, language_id="ru")
ta.save("russian.wav", wav, model.sr)

# Turkish
turkish = "Merhaba, nasılsınız?"
wav = model.generate(turkish, language_id="tr")
ta.save("turkish.wav", wav, model.sr)

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Voice Cloning Across Languages

You can clone a voice from one language and use it to speak another language: 
# Use an English voice reference to speak French
wav = model.generate(
    "Bonjour, comment ça va?",
    language_id="fr",
    audio_prompt_path="english_speaker.wav"
)
Accent Transfer: When using a reference voice from one language to generate speech in another, the output may inherit the accent of the reference language. See the tips below for managing this.

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Accent and Language Transfer

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Understanding Accent Transfer

When you use a voice from Language A to generate speech in Language B, the model may produce speech with an accent characteristic of Language A: 
# English speaker generating Spanish - may have English accent
wav = model.generate(
    "Hola, ¿cómo estás?",
    language_id="es",
    audio_prompt_path="native_english_speaker.wav"
)

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Reducing Accent Transfer

To minimize accent transfer and get more native-sounding pronunciation, set cfg_weight=0: 
# Reduce accent transfer from reference audio
wav = model.generate(
    "Hola, ¿cómo estás?",
    language_id="es",
    audio_prompt_path="english_speaker.wav",
    cfg_weight=0.0  # Reduces accent influence
)
From the README: “Ensure that the reference clip matches the specified language tag. Otherwise, language transfer outputs may inherit the accent of the reference clip’s language. To mitigate this, set cfg_weight to 0.”

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When to Use Accent Transfer

Sometimes accent transfer is desirable:
  • Creating characters with foreign accents
  • Representing non-native speakers authentically
  • Maintaining voice consistency across languages for a specific character
# Intentionally keep the accent for character consistency
wav = model.generate(
    "Buenos días",
    language_id="es",
    audio_prompt_path="character_voice.wav",
    cfg_weight=0.5  # Maintain accent
)

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Configuration Tips from README

The README provides specific guidance for multilingual usage:

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General Use

Default Settings: The default settings (exaggeration=0.5, cfg_weight=0.5) work well for most prompts across all languages.
# Recommended defaults
wav = model.generate(
    text,
    language_id="fr",
    exaggeration=0.5,  # Default
    cfg_weight=0.5      # Default
)

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Fast Speaking Reference

If your reference speaker has a fast speaking style, lower cfg_weight: 
# For fast-speaking reference audio
wav = model.generate(
    text,
    language_id="es",
    audio_prompt_path="fast_speaker.wav",
    cfg_weight=0.3  # Improves pacing
)

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Matching Reference Language

For best results, match the reference audio language to your target language: 
# Best: French reference for French synthesis
wav = model.generate(
    "Bonjour!",
    language_id="fr",
    audio_prompt_path="french_speaker.wav"
)

# Acceptable: English reference for French (may have accent)
wav = model.generate(
    "Bonjour!",
    language_id="fr",
    audio_prompt_path="english_speaker.wav",
    cfg_weight=0.0  # Reduce accent
)

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Complete Multilingual Example

import torchaudio as ta
import torch
from chatterbox.mtl_tts import ChatterboxMultilingualTTS

# Auto-detect device
if torch.cuda.is_available():
    device = "cuda"
elif torch.backends.mps.is_available():
    device = "mps"
else:
    device = "cpu"

print(f"Using device: {device}")

# Initialize model
model = ChatterboxMultilingualTTS.from_pretrained(device=device)

# Generate in multiple languages
languages = [
    ("Hello, how are you today?", "en", "english.wav"),
    ("Bonjour, comment ça va?", "fr", "french.wav"),
    ("Hola, ¿cómo estás?", "es", "spanish.wav"),
    ("你好，今天天气真不错。", "zh", "chinese.wav"),
]

for text, lang_id, output_file in languages:
    print(f"Generating {lang_id}...")
    wav = model.generate(text, language_id=lang_id)
    ta.save(output_file, wav, model.sr)
    print(f"Saved {output_file}")

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Model Selection

Choose the right model for your needs:
Use CaseRecommended Model
English onlyChatterbox or Chatterbox Turbo
Multiple languagesChatterbox Multilingual
English with paralinguistic tagsChatterbox Turbo
Global applicationsChatterbox Multilingual
Low-latency voice agents (English)Chatterbox Turbo

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Punctuation Handling

The multilingual model handles language-specific punctuation: 
# Chinese punctuation (from mtl_tts.py:86)
sentence_enders = {".", "!", "?", "-", ",", "、", "，", "。", "？", "！"}
The model automatically normalizes punctuation for each language.

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Advanced Configuration

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Full Parameter Example

wav = model.generate(
    text="Votre texte ici",
    language_id="fr",
    audio_prompt_path="reference.wav",
    exaggeration=0.5,      # Expressiveness
    cfg_weight=0.5,        # Conditioning strength
    temperature=0.8,       # Sampling randomness
    repetition_penalty=2.0, # Reduce repetition
    min_p=0.05,           # Min probability threshold
    top_p=1.0             # Nucleus sampling
)
See the Configuration guide for detailed parameter explanations.

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Troubleshooting

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Unsupported Language Error

# Error: ValueError: Unsupported language_id 'xx'
languages = ChatterboxMultilingualTTS.get_supported_languages()
print(f"Supported: {list(languages.keys())}")

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Poor Pronunciation

  1. Ensure correct language_id - Verify you’re using the right code
  2. Check text encoding - Use UTF-8 for non-Latin scripts
  3. Adjust cfg_weight - Try cfg_weight=0.0 for more native pronunciation
  4. Use native reference audio - Match reference language to target language

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Strong Accent

If the accent from reference audio is too strong: 
# Minimize accent influence
wav = model.generate(
    text,
    language_id="target_language",
    audio_prompt_path="reference.wav",
    cfg_weight=0.0  # Removes most accent influence
)

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