This is a light version of chatterbox that removes:

• librosa and all its required dependencies and instead uses torchaudio and scipy
• perth because who the heck needs watermarking anyways
• omegaconf and instead use standard python
• others I forget, but everything works

However, I did add soundfile because I like it.

Installation

Go through these steps in order.

python -m venv .

.\Scripts\activate

python.exe -m pip install --upgrade pip

pip install uv

Next, make sure appropriate versions of torch, torchaudio, and CUDA are installed. Use torch 2.6 or newer, because transformers 5.20 and later won't use older versions.

uv pip install chatterbox-light

To install the latest code from GitHub instead:

uv pip install -r requirements.txt

pip install git+https://github.com/BBC-Esq/chatterbox-light.git --no-deps

This package installs the chatterbox module, just like Resemble AI's chatterbox-tts, so don't install both in one environment. Installs of this fork made from GitHub before version 1.0.1 are also named chatterbox-tts; run pip uninstall chatterbox-tts before installing this.

Optional: if you'll use the multilingual model with Japanese or Chinese text, also install these (or install "chatterbox-light[multilingual]"). Without them, Japanese kanji are dropped and Chinese text isn't split into words. The first time Chinese text is used, spacy-pkuseg downloads a ~35 MB model to ~/.pkuseg.

uv pip install pykakasi spacy-pkuseg

Usage

Each model's generate() returns a (1, samples) tensor at model.sr (24 kHz). Models download from Hugging Face the first time they're used. Save the audio with soundfile:

import soundfile as sf
sf.write("output.wav", wav.squeeze(0).numpy(), model.sr)

Chatterbox (English)

from chatterbox.tts import ChatterboxTTS

model = ChatterboxTTS.from_pretrained(device="cuda")  # or "cpu" / "mps"
wav = model.generate("Hello there, this is Chatterbox.")

# clone a voice from a reference clip
wav = model.generate("Hello there, this is Chatterbox.", audio_prompt_path="reference.wav")

# more expressive: raise exaggeration (default 0.5) and lower cfg_weight (default 0.5) for slower pacing
wav = model.generate("Hello there, this is Chatterbox.", exaggeration=0.7, cfg_weight=0.3)

Chatterbox Turbo (English)

Faster, and understands paralinguistic tags such as [laugh], [chuckle] and [cough]. A reference clip must be longer than 5 seconds. cfg_weight, exaggeration and min_p are ignored.

from chatterbox.tts_turbo import ChatterboxTurboTTS

model = ChatterboxTurboTTS.from_pretrained(device="cuda")
wav = model.generate("Hi there [chuckle], have you got a minute to chat?", audio_prompt_path="reference.wav")

Chatterbox Nano (English)

A smaller version of Turbo for CPU and tight memory budgets, loaded through the same class with nano=True:

from chatterbox.tts_turbo import ChatterboxTurboTTS

model = ChatterboxTurboTTS.from_pretrained(device="cpu", nano=True)
wav = model.generate("Hi there [chuckle], have you got a minute to chat?")

Chatterbox Multilingual (23 languages)

The v2 checkpoint loads by default. Pass t3_model="v3" for the newer v3 checkpoint, which upstream recommends (fewer hallucinations, better speaker similarity). For Japanese or Chinese text, install the optional packages above.

from chatterbox.mtl_tts import ChatterboxMultilingualTTS, SUPPORTED_LANGUAGES

print(SUPPORTED_LANGUAGES)  # language codes such as "fr", "de", "ja", "zh"
model = ChatterboxMultilingualTTS.from_pretrained(device="cuda", t3_model="v3")
wav = model.generate("Bonjour, comment ça va ?", language_id="fr")
wav = model.generate("Hola, ¿cómo estás?", language_id="es", audio_prompt_path="reference.wav")

Voice conversion

from chatterbox.vc import ChatterboxVC

model = ChatterboxVC.from_pretrained(device="cuda")
wav = model.generate("input.wav", target_voice_path="target_voice.wav")

See the example_*.py scripts for complete runs.

Enjoy!