  This paper presents a simple method for speech videos generation based on
audio: given a piece of audio, we can generate a video of the target face
speaking this audio. We propose Generative Adversarial Networks (GAN) with cut
speech audio input as condition and use Convolutional Gate Recurrent Unit (GRU)
in generator and discriminator. Our model is trained by exploiting the short
audio and the frames in this duration. For training, we cut the audio and
extract the face in the corresponding frames. We designed a simple encoder and
compare the generated frames using GAN with and without GRU. We use GRU for
temporally coherent frames and the results show that short audio can produce
relatively realistic output results.
