  This study delves into the intricacies of synchronizing facial dynamics with
multilingual audio inputs, focusing on the creation of visually compelling,
time-synchronized animations through diffusion-based techniques. Diverging from
traditional parametric models for facial animation, our approach, termed
LinguaLinker, adopts a holistic diffusion-based framework that integrates
audio-driven visual synthesis to enhance the synergy between auditory stimuli
and visual responses. We process audio features separately and derive the
corresponding control gates, which implicitly govern the movements in the
mouth, eyes, and head, irrespective of the portrait's origin. The advanced
audio-driven visual synthesis mechanism provides nuanced control but keeps the
compatibility of output video and input audio, allowing for a more tailored and
effective portrayal of distinct personas across different languages. The
significant improvements in the fidelity of animated portraits, the accuracy of
lip-syncing, and the appropriate motion variations achieved by our method
render it a versatile tool for animating any portrait in any language.
