ChatTTS.com
C
Chattts.com
Overview :
ChatTTS is a voice generation model designed for conversational scenarios, particularly suitable for dialogue tasks of large language model assistants and conversational audio and video introductions. It supports both English and Chinese and showcases high-quality and natural speech synthesis capabilities through training on approximately 100,000 hours of English and Chinese data.
Target Users :
ChatTTS is designed for developers, academic researchers, and anyone who needs to convert text into speech for their applications or services. It is especially suited for conversational applications that require high-quality, natural-sounding speech synthesis, such as language model assistants, video introductions, and educational and training content.
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Top Region: CN(51.36%)
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Use Cases
Dialogue tasks for large language model assistants
Generating voiceovers for conversational video introductions
Speech synthesis for educational and training content
Features
Multilingual Support: Includes English and Chinese, overcoming language barriers.
Extensive Data Training: Trained on approximately 10 million hours of English and Chinese data to generate high-quality, natural-sounding speech.
Conversational Task Compatibility: Suitable for handling dialogue tasks of large language models, providing a natural and fluid interaction experience.
Open-Source Initiative: Plans to open-source the training base model to promote academic research and community development.
Control and Security: Committed to improving the model's controllability, adding watermarks, and integrating it into large language models.
Ease of Use: Generates corresponding voice files from text information, making it simple and convenient to use.
How to Use
Download the code from GitHub
Install necessary dependency packages, such as torch and ChatTTS
Import the required libraries, including torch, ChatTTS, and IPython.display's Audio
Create an instance of the ChatTTS class and load the pre-trained model
Define the text to be converted into speech
Use the infer method to generate speech from the text, set use_decoder=True to enable the decoder
Play the generated audio using IPython.display's Audio class
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