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chatterbox

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README.md
Chatterbox-Multilingual

Chatterbox TTS

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_Made with ♥️ by resemble-logo-horizontal

We're excited to introduce Chatterbox Multilingual, Resemble AI's 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.. Or try the multilingual version on our Multilingual Hugging Face Gradio app..

If you like the model but need to scale or tune it for higher accuracy, check out our competitively priced TTS service (link). 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

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

Alternatively, you can install from source:

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

See

example_tts.py
and
example_vc.py
for more examples.

Acknowledgements

Built-in PerTh Watermarking for Responsible AI

Every audio file generated by Chatterbox includes Resemble AI's Perth (Perceptual Threshold) Watermarker - 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.

Official Discord

👋 Join us on Discord 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.