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ChatTTS: Open Source Generative Speech Model Review

Updated on Sep 15,2025

Table of Contents

In the ever-evolving landscape of AI and machine learning, Text-to-Speech (TTS) technology has made significant strides. ChatTTS, an open-source generative speech model designed for daily dialogue scenarios, is one such innovation. This article explores ChatTTS, examining its features, installation process, and overall performance. Whether you're a developer or simply curious about the latest in AI speech models, this review provides a comprehensive overview of ChatTTS and its potential applications.

Key Points

ChatTTS is an open-source generative speech model for daily dialogue.

It supports both English and Chinese languages.

The model is trained with over 100,000+ hours of speech data.

Installation requires cloning the GitHub repository and installing dependencies.

The model's audio quality is noted to be impressive but comes with slower processing times.

Exploring ChatTTS: An Open-Source TTS Revolution

What is ChatTTS?

ChatTTS

is a Text-to-Speech model specifically designed for dialogue scenarios, operating as a ULM (Universal Language Model) assistant. It’s open-source and designed for daily dialogue use cases, aiming to provide natural and expressive Speech Synthesis. The model supports both English and Chinese languages and is trained with 100,000+ hours of speech data. Its conversational nature aims to enable natural interactions, including prosody features like laughter and pauses.

Key Features:

  • Open-source and accessible for various applications.
  • Designed specifically for dialogue-based interactions.
  • Supports mixed language input.
  • Offers multi-speaker capabilities.
  • Allows precise control over prosodic elements, including laughter, pauses, and intonation.
  • Provides natural and expressive speech delivery.

Gaining Traction: Popularity on GitHub

ChatTTS is becoming increasingly popular within the open-source community. With almost 20,000 stars on GitHub

, the project is gaining a lot of attention. Being open-source allows developers to use and modify the model for various purposes, contributing to its popularity. This visibility and community support make it a promising tool for developers and researchers. The fact that it's gaining this traction in the open-source world is a big sign that it's worth checking out.

Setting Up ChatTTS Locally

Step-by-Step Installation Guide

To set up ChatTTS on your local machine, follow these steps:

  1. Clone the GitHub Repository: Use the command git clone https://github.com/2noise/ChatTTS.git

    in your terminal.

  2. Navigate to the Directory: Change the directory to the cloned repository using cd ChatTTS .
  3. Install Dependencies: Install the necessary Python packages using pip install -r requirements.txt .

After completing these steps, ChatTTS should be installed and ready for use on your local system. The presenter mentioned they had already installed it so there should be no problems with the process.

Note: Check to ensure you have PyTorch installed before running the dependency command, this package can cause issues if installed incorrectly. The installation steps are clearly laid out in the Github, making it easier for you to get running.

Basic Usage: Running a Simple Text-to-Speech Conversion

Here’s how to run a basic text-to-speech conversion with ChatTTS. This example is adapted from the GitHub documentation

:

import ChatTTS
from IPython.display import Audio
import torch
import torchaudio

chat = ChatTTS.Chat()
chat.load_models(compile=False)  # Set to True for better performance

texts = ["PUT YOUR TEXT HERE"]

wavs = chat.infer(texts)
torchaudio.save("output1.wav", torch.from_numpy(wavs[0]), 24000)
  1. Import Necessary Libraries: Import the required modules from ChatTTS, IPython, and torchaudio .
  2. Initialize ChatTTS: Create an instance of the ChatTTS model.
  3. Load Models: Load the pre-trained models using the load_models method.
  4. Define Text: Specify the text you want to convert to speech.
  5. Infer Speech: Use the infer method to generate the audio data.
  6. Save the Audio: Save the generated audio data to a WAV file using torchaudio.save.

However, there was a bit of a problem during the running of the script, with torch audio not being defined. But this was fixed with a simple import statement.

Note: Make sure that you have a strong enough system to run this model. As the presenter notes, if you run this on your local computer, it may take a while.

Advanced Usage: Injecting Emotion

One exciting aspect of ChatTTS is the ability to inject emotional cues into the synthesized speech. This is achieved through special tokens like [uv_break] (pauses) and [laugh] (laughter)

. Here’s an example of how to use these tokens:

import ChatTTS
from IPython.display import Audio
import torch
import torchaudio

inputs_en = """
ChatTTS is a text to speech model designed for dialogue applications.
[uv_break] It supports mixed language input [uv_break]and offers multi speaker
capabilities with precise control over prosodic elements [laugh]like like
[uv_break]laughter[laugh], [uv_break]pauses, [uv_break]and intonation.
[uv_break]It delivers natural and expressive speech,[uv_break]so please
[uv_break] use the project responsibly at your own risk.[uv_break]"""

param_refine_text = {"prompt": ["oral_2"][laugh_6][break_4]}
audio_array_cn = chat.infer(inputs_en, param_refine_text=param_refine_text)
torchaudio.save("output3.wav", torch.from_numpy(audio_array_cn[0]), 24000)

With some more tweaking, you can also get different voices to output, with the male voice seeming to have less emotion included.

ChatTTS Usage Guide

Clone the Repository

Start by cloning the ChatTTS GitHub repository to your local machine using Git. This will give you access to all the necessary files and scripts.

git clone https://github.com/2noise/ChatTTS.git

Install Dependencies

Navigate into the cloned directory and install the required Python packages using pip. This will ensure that you have all the necessary libraries to run ChatTTS.

cd ChatTTS
pip install -r requirements.txt

Run a Simple TTS Conversion

Use the basic usage script from the previous section (basic usage, setting up ChatTTS). Replace the dummy text with whatever you want to output. Run your script to output your text to audio.

Pricing

Open Source Accessibility

ChatTTS, being open-source, is free to use. This makes it a cost-effective solution for various projects, especially for those looking to experiment with TTS technology without incurring licensing fees. Costs may arise from computational resources if running locally.

Evaluating ChatTTS: Advantages and Disadvantages

👍 Pros

Open-source and free to use.

High-quality speech synthesis with natural expressiveness.

Supports both English and Chinese.

Offers multi-speaker capabilities and prosodic control.

👎 Cons

Slower processing times may not be ideal for real-time applications.

Lack of direct voice control can make voice outputs unpredictable.

Requires setup and dependency management.

Requires higher end hardware to achieve faster processing times.

Core Features

Language Support and Expressiveness

With both English and Chinese support and the ability to inject emotional cues, ChatTTS offers rich expressive possibilities. This makes it well-suited for dialogue applications needing a wide range of emotional tones and language flexibility.

Ideal Use Cases for ChatTTS

Applications in Dialogue Systems

ChatTTS is particularly valuable in developing dialogue systems and conversational agents that require natural, expressive voice output. This includes virtual assistants, interactive story-telling applications, and educational tools that benefit from nuanced speech delivery.

FAQ

Is ChatTTS free to use?
Yes, ChatTTS is an open-source project licensed under the MIT license, allowing it to be used free of charge for personal and commercial purposes.
What languages does ChatTTS support?
ChatTTS natively supports both English and Chinese, making it accessible to a broad range of users and developers.
Can I use ChatTTS for real-time speech synthesis?
While ChatTTS delivers high-quality audio, the processing times may be slower compared to proprietary solutions, making it less ideal for real-time applications without optimization.
What are the system requirements for running ChatTTS locally?
Running ChatTTS locally requires a suitable Python environment and depends on PyTorch. While specifics will differ based on the version, a reasonably powered modern PC should be able to easily use the model.

Related Questions

How does ChatTTS compare to other open-source TTS models?
ChatTTS distinguishes itself with its focus on dialogue and expressive speech, setting it apart from more general-purpose TTS models. Its integration of emotional tokens and multi-speaker capabilities provide advanced features that are not commonly found in other open-source alternatives. That being said, there are some other open source models, such as MozillaTTS, that have very similar functionalities.
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