ChatTTS is a voice generation model,Chat TTS is specifically designed for conversational scenarios.
ChatTTS: Text-to-Speech For Chat
ChatTTS is a voice generation model on GitHub at 2noise/chattts,Chat TTS is specifically designed for conversational scenarios. It is ideal for applications such as dialogue tasks for large language model assistants, as well as conversational audio and video introductions. The model supports both Chinese and English, demonstrating high quality and naturalness in speech synthesis. This level of performance is achieved through training on approximately 100,000 hours of Chinese and English data. Additionally, the project team plans to open-source a basic model trained with 40,000 hours of data, which will aid the academic and developer communities in further research and development.
ChatTTS Features
1)Multi-language Support
One of the key features of ChatTTS is its support for multiple languages, including English and Chinese. This allows it to serve a wide range of users and overcome language barriers
2)Large Data Training
ChatTTS has been trained using a significant amount of data, approximately 10 million hours of Chinese and English data. This extensive training has resulted in high-quality and natural-sounding voice synthesis
3)Dialog Task Compatibility
ChatTTS is well-suited for handling dialog tasks typically assigned to large language models LLMs. It can generate responses for conversations and provide a more natural and fluid interaction experience when integrated into various applications and services
4)Open Source Plans
the project team plans to open source a trained base model. This will enable academic researchers and developers in the community to further study and develop the technology
5)Control and Security
The team is committed to improving the controllability of the model, adding watermarks, and integrating it with LLMs. These efforts ensure the safety and reliability of the model
6)Ease of Use
ChatTTS provides an easy-to-use experience for its users. It requires only text information as input, which generates corresponding voice files. This simplicity makes it convenient for users who have voice synthesis needs