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chatterbox
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---

title: chatterbox
app_file: gradio_tts_app.py
sdk: gradio
sdk_version: 4.44.1
---


<img width="1200" alt="cb-big2" src="https://github.com/user-attachments/assets/bd8c5f03-e91d-4ee5-b680-57355da204d1" />

# 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)

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

We're excited to introduce Chatterbox, [Resemble AI's](https://resemble.ai) first production-grade open source TTS model. 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. It's also the first open source TTS model to support **emotion exaggeration control**, a powerful feature that makes your voices stand out. Try it now on our [Hugging Face Gradio app.](https://huggingface.co/spaces/ResembleAI/Chatterbox)

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
- SoTA zeroshot 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)

# Tips
- **General Use (TTS and Voice Agents):**
  - The default settings (`exaggeration=0.5`, `cfg_weight=0.5`) work well for most prompts.
  - 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
```

pip install chatterbox-tts

```


# Usage
```python

import torchaudio as ta

from chatterbox.tts import ChatterboxTTS



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-1.wav", wav, 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` 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.

# Disclaimer
Don't use this model to do bad things. Prompts are sourced from freely available data on the internet.