The recent advancements in audio-driven talking face generation have significantly enhanced the realism and customization capabilities of generated videos. Researchers are focusing on improving temporal coherence, visual quality, and the ability to control specific features such as gaze orientation and emotional expression. Key innovations include the use of latent diffusion models for better audio-visual correlation, dynamic lip point clouds for 3D talking head synthesis, and facial landmark transformations to enhance facial consistency in video generation. Additionally, frameworks are being developed to allow for high-quality, emotion-controllable movie dubbing, addressing the dual challenges of audio-visual synchronization and clear pronunciation. Notably, methods integrating gaze orientation and highly disentangled portrait animation are emerging as powerful tools for generating realistic and expressive talking faces. These developments collectively push the boundaries of what is possible in digital communication and character animation.