Abstract
Speech driven facial animation can be regarded as a speech-to-face translation. Speech driven facial motion synthesis involves Speech analysis and face modeling. This method makes use of still image of a person and speech signals to produce an animation of a talking character. Our method makes use of GAN classifier to obtain better lip synchronizing with audio. GAN methodology also helps to obtain realistic facial expressions thereby making a talking character more effective. Factors such as lip-syncing accuracy, sharpness, and ability to create high -quality faces and natural blinks are taken into consideration by this system. GANs are mainly used in case of image generation as adversarial loss generates sharper and more depictive images. Along with images, GANs can also handle videos easily.
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