
<img width="1200" alt="Chatterbox Multilingual" src="https://github.com/user-attachments/assets/53b411b4-d7b8-4b18-87f3-335145837684" />


# Chatterbox TTS

[![Alt Text](https://img.shields.io/badge/listen-demo_samples-blue)](https://resemble-ai.github.io/chatterbox_demopage/)
[![Alt Text](https://huggingface.co/datasets/huggingface/badges/resolve/main/open-in-hf-spaces-sm.svg)](https://huggingface.co/spaces/ResembleAI/Chatterbox)
[![Alt Text](https://static-public.podonos.com/badges/insight-on-pdns-sm-dark.svg)](https://podonos.com/resembleai/chatterbox)
[![Discord](https://img.shields.io/discord/1377773249798344776?label=join%20discord&logo=discord&style=flat)](https://discord.gg/rJq9cRJBJ6)

_Made with ♥️ by <a href="https://resemble.ai" target="_blank"><img width="100" alt="resemble-logo-horizontal" src="https://github.com/user-attachments/assets/35cf756b-3506-4943-9c72-c05ddfa4e525" /></a>

We're excited to introduce **Chatterbox Multilingual**, [Resemble AI's](https://resemble.ai) first production-grade open source TTS model supporting **23 languages** out of the box. Licensed under MIT, Chatterbox has been benchmarked against leading closed-source systems like ElevenLabs, and is consistently preferred in side-by-side evaluations.

Whether you're working on memes, videos, games, or AI agents, Chatterbox brings your content to life across languages. It's also the first open source TTS model to support **emotion exaggeration control** with robust **multilingual zero-shot voice cloning**. Try the english only version now on our [English Hugging Face Gradio app.](https://huggingface.co/spaces/ResembleAI/Chatterbox). Or try the multilingual version on our [Multilingual Hugging Face Gradio app.](https://huggingface.co/spaces/ResembleAI/Chatterbox-Multilingual-TTS).

If you like the model but need to scale or tune it for higher accuracy, check out our competitively priced TTS service (<a href="https://resemble.ai">link</a>). It delivers reliable performance with ultra-low latency of sub 200ms—ideal for production use in agents, applications, or interactive media.

# Key Details
- Multilingual, zero-shot TTS supporting 23 languages
- SoTA zeroshot English TTS
- 0.5B Llama backbone
- Unique exaggeration/intensity control
- Ultra-stable with alignment-informed inference
- Trained on 0.5M hours of cleaned data
- Watermarked outputs
- Easy voice conversion script
- [Outperforms ElevenLabs](https://podonos.com/resembleai/chatterbox)

# Supported Languages 
Arabic (ar) • Danish (da) • German (de) • Greek (el) • English (en) • Spanish (es) • Finnish (fi) • French (fr) • Hebrew (he) • Hindi (hi) • Italian (it) • Japanese (ja) • Korean (ko) • Malay (ms) • Dutch (nl) • Norwegian (no) • Polish (pl) • Portuguese (pt) • Russian (ru) • Swedish (sv) • Swahili (sw) • Turkish (tr) • Chinese (zh)
# Tips
- **General Use (TTS and Voice Agents):**
  - 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`.
  - The default settings (`exaggeration=0.5`, `cfg_weight=0.5`) work well for most prompts across all languages.
  - If the reference speaker has a fast speaking style, lowering `cfg_weight` to around `0.3` can improve pacing.

- **Expressive or Dramatic Speech:**
  - Try lower `cfg_weight` values (e.g. `~0.3`) and increase `exaggeration` to around `0.7` or higher.
  - Higher `exaggeration` tends to speed up speech; reducing `cfg_weight` helps compensate with slower, more deliberate pacing.


# Installation
```shell
pip install chatterbox-tts
```

Alternatively, you can install from source:
```shell
# conda create -yn chatterbox python=3.11
# conda activate chatterbox

git clone https://github.com/resemble-ai/chatterbox.git
cd chatterbox
pip install -e .
```
We developed and tested Chatterbox on Python 3.11 on Debian 11 OS; the versions of the dependencies are pinned in `pyproject.toml` to ensure consistency. You can modify the code or dependencies in this installation mode.

# Usage
```python
import torchaudio as ta
from chatterbox.tts import ChatterboxTTS


# English example
model = ChatterboxTTS.from_pretrained(device="cuda")

text = "Ezreal and Jinx teamed up with Ahri, Yasuo, and Teemo to take down the enemy's Nexus in an epic late-game pentakill."
wav = model.generate(text)
ta.save("test-english.wav", wav, model.sr)

# Multilingual examples
multilingual_model = ChatterboxMultilingualTTS.from_pretrained(device=device)

french_text = "Bonjour, comment ça va? Ceci est le modèle de synthèse vocale multilingue Chatterbox, il prend en charge 23 langues."
wav_french = multilingual_model.generate(spanish_text, language_id="fr")
ta.save("test-french.wav", wav_french, model.sr)

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

# If you want to synthesize with a different voice, specify the audio prompt
AUDIO_PROMPT_PATH = "YOUR_FILE.wav"
wav = model.generate(text, audio_prompt_path=AUDIO_PROMPT_PATH)
ta.save("test-2.wav", wav, model.sr)
```
See `example_tts.py` and `example_vc.py` for more examples.

# Acknowledgements
- [Cosyvoice](https://github.com/FunAudioLLM/CosyVoice)
- [Real-Time-Voice-Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning)
- [HiFT-GAN](https://github.com/yl4579/HiFTNet)
- [Llama 3](https://github.com/meta-llama/llama3)
- [S3Tokenizer](https://github.com/xingchensong/S3Tokenizer)

# Built-in PerTh Watermarking for Responsible AI

Every audio file generated by Chatterbox includes [Resemble AI's Perth (Perceptual Threshold) Watermarker](https://github.com/resemble-ai/perth) - imperceptible neural watermarks that survive MP3 compression, audio editing, and common manipulations while maintaining nearly 100% detection accuracy.


## Watermark extraction

You can look for the watermark using the following script.

```python
import perth
import librosa

AUDIO_PATH = "YOUR_FILE.wav"

# Load the watermarked audio
watermarked_audio, sr = librosa.load(AUDIO_PATH, sr=None)

# Initialize watermarker (same as used for embedding)
watermarker = perth.PerthImplicitWatermarker()

# Extract watermark
watermark = watermarker.get_watermark(watermarked_audio, sample_rate=sr)
print(f"Extracted watermark: {watermark}")
# Output: 0.0 (no watermark) or 1.0 (watermarked)
```


# Official Discord

👋 Join us on [Discord](https://discord.gg/rJq9cRJBJ6) and let's build something awesome together!

# Citation
If you find this model useful, please consider citing.
```
@misc{chatterboxtts2025,
  author       = {{Resemble AI}},
  title        = {{Chatterbox-TTS}},
  year         = {2025},
  howpublished = {\url{https://github.com/resemble-ai/chatterbox}},
  note         = {GitHub repository}
}
```
# Disclaimer
Don't use this model to do bad things. Prompts are sourced from freely available data on the internet.
