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Towards EEG-based Talking-face Generation for Brain Signal-driven Dynamic Communication.

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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    Area of Science:

    • Neuroscience
    • Computer Science
    • Biomedical Engineering

    Background:

    • Decoding speech and generating images from brain activity shows promise for neuroprosthetics and communication.
    • Previous methods produced fragmented outputs, limiting their use as alternative communication.

    Purpose of the Study:

    • To develop an integrated framework for synthesizing speech and generating lip-synced talking-faces from non-invasive brain signals.
    • To enable realistic and dynamic brain signal-mediated communication using personalized faces (real or avatar).

    Main Methods:

    • Utilized non-invasive speech-related brain signals.
    • Developed an integrated framework to synthesize speech and generate talking-faces.
    • Employed denoising techniques to enhance voice quality and minimize facial artifacts.
    • Personalized talking-faces using real faces or avatars.

    Main Results:

    • Successfully generated clear and natural talking-faces from noisy brain signals.
    • Achieved dynamic communication through integrated speech and visual interfaces.
    • Demonstrated applicability to both real faces and avatars.

    Conclusions:

    • The proposed framework significantly advances brain signal-driven face-to-face communication.
    • This integrated approach represents a major step towards intuitive and dynamic brain-computer interface communication systems.