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Turns a one-line request in your AI agent into a finished design: a launch animation, a clickable app prototype, an editable slide deck, an infographic or a se…
Speaks English text aloud with a 350M-parameter model built for low-latency voice agents, and adds laughs and coughs through tags in the text. Suits developers who want quick, expressive speech with less GPU memory.
Chatterbox-Turbo is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install chatterbox-tts
Chatterbox-Turbo is an open-source text-to-speech model from Resemble AI, one of three models in the Chatterbox family. It has about 350 million parameters and speaks English. The maker cut the mel decoder from 10 steps to one, so it needs less compute and video memory than earlier models.
Developers who build voice agents, narration or other speech features and want expressive output, under the MIT license.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Voice products | Agent builders | Give a voice agent fast, natural speech | Call back a customer with a spoken reply |
| Media | Content creators | Narrate scripts with laughs and coughs | Add a chuckle to a line |
| Software | App developers | Add spoken output to an app | Read a message aloud |
| Customer service | Support teams | Test a phone-style voice assistant | Prototype a billing call |
Skip it if you need languages other than English, since the Multilingual model in the same family covers more than 23.
It runs in Python, and the card's example loads it on a CUDA GPU.
| Use case | Who | What they get back |
|---|---|---|
| Voice agents | Agent builders | Low-latency spoken replies |
| Narration | Creators | Speech with tags marking laughs, coughs and chuckles |
| App speech | Developers | Audio files made from text |
You need Python and the chatterbox-tts package.
pip install chatterbox-tts
pip install -U huggingface_hub hf download ResembleAI/chatterbox-turbo
Import the Turbo class, load the model, then pass it text that may hold paralinguistic tags. The card begins its example like this.
import torchaudio as ta import torch from chatterbox.tts_turbo import ChatterboxTurboTTS model = ChatterboxTurboTTS.from_pretrained(device="cuda")
| Tool | What it does |
|---|---|
| ChatterboxTurboTTS | Loads and runs the Turbo model |
| from_pretrained | Fetches the weights and puts them on the chosen device |
| [laugh] | Tag that adds a laugh to the speech |
| [cough] | Tag that adds a cough |
| [chuckle] | Tag that adds a chuckle |
You write a short English line for a phone call and place a chuckle tag in the middle. The model speaks the line as audio, and the chuckle lands where you put the tag.
If you are new to text to speech, install the package, load the model and say one short sentence. Then add a tag to hear how it changes the delivery.
If you know the field, Turbo uses a lean 350M design. The speech-token-to-mel decoder was distilled so generation takes one step instead of ten, while the maker says audio fidelity stays high. Tags are native to the model, which is built mainly for low-latency agents.
The family also has Multilingual and the original Chatterbox, and the card says Multilingual offers zero-shot cloning. Use only voices you have the right to use.
Speaks English text aloud with a 350M-parameter model built for low-latency voice agents, and adds laughs and coughs through tags in the text. Suits developers who want quick, expressive speech with less GPU memory.
Made by ResembleAI on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.
What it is: Chatterbox-Turbo is an open-source text-to-speech model from Resemble AI, one of three models in the Chatterbox family. It has about 350 million parameters and speaks English. The maker cut the mel decoder from 10 steps to one, so it needs less compute and video memory than earlier models.
Who it suits: Developers who build voice agents, narration or other speech features and want expressive output, under the MIT license.
Industry | Who uses it | How they use it | Example
Voice products | Agent builders | Give a voice agent fast, natural speech | Call back a customer with a spoken reply
Media | Content creators | Narrate scripts with laughs and coughs | Add a chuckle to a line
Software | App developers | Add spoken output to an app | Read a message aloud
Customer service | Support teams | Test a phone-style voice assistant | Prototype a billing call
Skip it if you need languages other than English, since the Multilingual model in the same family covers more than 23.
Where to use it: It runs in Python, and the card's example loads it on a CUDA GPU.
Use case | Who | What they get back
Voice agents | Agent builders | Low-latency spoken replies
Narration | Creators | Speech with tags marking laughs, coughs and chuckles
App speech | Developers | Audio files made from text
How to set it up: You need Python and the chatterbox-tts package.
pip install chatterbox-tts
pip install -U huggingface_hub
hf download ResembleAI/chatterbox-turbo
How to use it: Import the Turbo class, load the model, then pass it text that may hold paralinguistic tags. The card begins its example like this.
import torchaudio as ta
import torch
from chatterbox.tts_turbo import ChatterboxTurboTTS
model = ChatterboxTurboTTS.from_pretrained(device="cuda")
Tool | What it does
ChatterboxTurboTTS | Loads and runs the Turbo model
from_pretrained | Fetches the weights and puts them on the chosen device
[laugh] | Tag that adds a laugh to the speech
[cough] | Tag that adds a cough
[chuckle] | Tag that adds a chuckle
Example: You write a short English line for a phone call and place a chuckle tag in the middle. The model speaks the line as audio, and the chuckle lands where you put the tag.
For newcomers and experts: If you are new to text to speech, install the package, load the model and say one short sentence. Then add a tag to hear how it changes the delivery.
If you know the field, Turbo uses a lean 350M design. The speech-token-to-mel decoder was distilled so generation takes one step instead of ten, while the maker says audio fidelity stays high. Tags are native to the model, which is built mainly for low-latency agents.
Install chatterbox-tts
Load the Turbo model
Write text with optional tags
Generate speech
Save or play the audio
Good to know: The family also has Multilingual and the original Chatterbox, and the card says Multilingual offers zero-shot cloning. Use only voices you have the right to use.
Title: Model size in the Chatterbox family
Turbo: 350 M
Multilingual: 500 M
Chatterbox: 500 M
Download its files with Hugging Face's command line:
pip install -U huggingface_hub
hf download ResembleAI/chatterbox-turbo
Then follow the usage in its model card. Nothing in this kit runs by itself.
README.md 5 KB
Listed Hugging Face models in the same category that share the most tags with this one.
| Product | Downloads, last 30 days | Likes | Parameters | License | Last change |
|---|---|---|---|---|---|
| Chatterbox-Turbo This page | 0 | 709 | — | mit | |
| Chatterbox TTSShares speech-generation · voice-cloning · speech | 2,440,902 | 1,911 | — | mit | |
| AuKShares speech-generation · voice-cloning · speech | 1,455 | 396 | — | mit | |
| Chatterbox-NanoShares speech-generation · voice-cloning · speech | 0 | 49 | — | mit | |
| Ming-3.0-tts-0.5B by inclusionAIShares speech-generation · voice-cloning · text-to-speech | 14,756 | 225 | 1.5B | mit | |
| Ming-3.0-tts-tinyShares speech-generation · voice-cloning · text-to-speech | 9,080 | 61 | 9B | mit |
Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search and on Trendshift. Mindket doesn’t write or check them. Open one to read it where it was posted.
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