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We're excited to introduce Chatterbox, Resemble AI's 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.
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.
General Use (TTS and Voice Agents):
exaggeration=0.5
, cfg_weight=0.5
) work well for most prompts.cfg_weight
to around 0.3
can improve pacing.Expressive or Dramatic Speech:
cfg_weight
values (e.g. ~0.3
) and increase exaggeration
to around 0.7
or higher.exaggeration
tends to speed up speech; reducing cfg_weight
helps compensate with slower, more deliberate pacing.pip install chatterbox-tts
Alternatively, you can install from source:
# 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 Debain 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.
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
and example_vc.py
for more examples.
Currenlty only English.
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.
You can look for the watermark using the following script.
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)
👋 Join us on Discord and let's build something awesome together!
Don't use this model to do bad things. Prompts are sourced from freely available data on the internet.
FAQs
Chatterbox: Open Source TTS and Voice Conversion by Resemble AI
We found that chatterbox-tts demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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