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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.

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Identifying People Expressions in Google Meets Calls
This is a complex task with several challenges:
* Technical Limitations: Google Meets doesn't currently offer an API to directly access facial expressions of participants.
* Privacy Concerns: Analyzing facial expressions raises significant privacy issues. Users should have control over whether their expressions are being tracked and used.
* Accuracy: Even with access to facial data, accurately interpreting expressions can be difficult due to variations in lighting, angles, and individual differences.
Possible Approaches (with limitations):
* User-Submitted Data: Participants could manually indicate their emotions during the call, which could be collected and analyzed. This relies on user honesty and may not capture subtle expressions.
* Third-Party Tools: Some external tools might analyze video feeds and attempt to detect expressions. However, their accuracy and privacy practices should be carefully evaluated.
* Future Developments: Google or other companies might develop features that allow for more ethical and accurate expression analysis in the future.
It's important to remember that facial expressions are just one aspect of communication, and relying solely on them can be misleading.

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