

DICE Talk
Overview :
DICE-Talk is an advanced technology for generating emotion-driven talking portraits. It can produce vivid and diverse emotional expressions. This technology uses diffusion models to decouple identity and emotion, providing realistic and diverse outputs. Its significance lies in bringing higher interactivity and expressiveness to areas such as virtual characters, animation, gaming, and social media, making it suitable for research and development needs.
Target Users :
DICE-Talk is suitable for target audiences such as animators, game developers, researchers, and social media content creators because it provides an engaging interaction with virtual figures, enhancing the attractiveness and realism of their work.
Use Cases
Use DICE-Talk in video games to create vivid expressions and dialogues for characters.
Make animated short films using DICE-Talk to enhance the emotive expression of characters.
Social media content creators use DICE-Talk to produce eye-catching virtual streamer content.
Features
Generate a variety of emotionally driven talking portraits
Support neutral, happy, angry, and surprised emotions
Provide an easy-to-use demo and graphical user interface
Support multiple input formats, including images and audio
Accelerate the generation process using high-performance GPUs
Compatible with multiple operating systems
Provide open source code for further research and development
Allow users to adjust the intensity of identity retention and emotional generation
How to Use
Ensure that required software and libraries are installed, including ffmpeg and PyTorch.
Download the model files to a specified directory using the huggingface-cli.
Use the demo.py script by providing input image and audio file paths.
Choose the desired emotional type and set parameters.
Run the script to generate a video of an emotional talking portrait.
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