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.

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!