Lip Sync

Lip synchronization (lip sync) in audio-visual content aims to create realistic-looking mouth movements that accurately match spoken audio. Current research heavily focuses on developing sophisticated deep learning models, often employing transformer networks and diffusion models, to generate high-fidelity talking faces with precise lip movements, while also controlling other facial features like head pose and expressions. These advancements are driven by the need for improved realism in applications such as virtual avatars, dubbing, and video editing, impacting fields ranging from entertainment to accessibility technologies. The ongoing emphasis is on achieving person-generic solutions that require minimal training data and maintain identity preservation, alongside the development of robust evaluation metrics for lip sync accuracy.