  Most earlier investigations on talking face generation have focused on the
synchronization of lip motion and speech content. However, human head pose and
facial emotions are equally important characteristics of natural human faces.
While audio-driven talking face generation has seen notable advancements,
existing methods either overlook facial emotions or are limited to specific
individuals and cannot be applied to arbitrary subjects. In this paper, we
propose a one-shot Talking Head Generation framework (SPEAK) that distinguishes
itself from general Talking Face Generation by enabling emotional and postural
control. Specifically, we introduce the Inter-Reconstructed Feature
Disentanglement (IRFD) method to decouple human facial features into three
latent spaces. We then design a face editing module that modifies speech
content and facial latent codes into a single latent space. Subsequently, we
present a novel generator that employs modified latent codes derived from the
editing module to regulate emotional expression, head poses, and speech content
in synthesizing facial animations. Extensive trials demonstrate that our method
can generate realistic talking head with coordinated lip motions, authentic
facial emotions, and smooth head movements. The demo video is available at the
anonymous link: https://anonymous.4open.science/r/SPEAK-F56E
