A computing device comprising: a processor; memory storing instructions, wherein the instructions, when executed by the processor, cause the processor to perform acts comprising: receiving an audio sequence comprising content features reflective of spoken words uttered by a speaker; generating, by a first generator of a machine learning model, latent content variables being facial features corresponding to mouth and lip movements of the audio sequence, based upon the content features of the audio sequence and features from a neutral face, wherein the latent content variables are to be used to synchronize movement of lips on a visual representation of a face to the spoken words uttered by the speaker; generating, by a second generator of the machine learning model, latent style variables being facial features corresponding to mouth movements of the audio sequence as well as other facial features defining together full facial features, based upon the audio sequence, the features from the neutral face, and the facial features output by the first generator, wherein the latent style variables are to be used to synchronize movement of the full facial features of the visual representation of the face to the spoken words uttered by the speaker; and causing the visual representation of the face to be animated on a display based upon the latent content variables and the latent style variables. a processor; memory storing instructions, wherein the instructions, when executed by the processor, cause the processor to perform acts comprising: receiving an audio sequence comprising content features reflective of spoken words uttered by a speaker; generating, by a first generator of a machine learning model, latent content variables being facial features corresponding to mouth and lip movements of the audio sequence, based upon the content features of the audio sequence and features from a neutral face, wherein the latent content variables are to be used to synchronize movement of lips on a visual representation of a face to the spoken words uttered by the speaker; generating, by a second generator of the machine learning model, latent style variables being facial features corresponding to mouth movements of the audio sequence as well as other facial features defining together full facial features, based upon the audio sequence, the features from the neutral face, and the facial features output by the first generator, wherein the latent style variables are to be used to synchronize movement of the full facial features of the visual representation of the face to the spoken words uttered by the speaker; and causing the visual representation of the face to be animated on a display based upon the latent content variables and the latent style variables. receiving an audio sequence comprising content features reflective of spoken words uttered by a speaker; generating, by a first generator of a machine learning model, latent content variables being facial features corresponding to mouth and lip movements of the audio sequence, based upon the content features of the audio sequence and features from a neutral face, wherein the latent content variables are to be used to synchronize movement of lips on a visual representation of a face to the spoken words uttered by the speaker; generating, by a second generator of the machine learning model, latent style variables being facial features corresponding to mouth movements of the audio sequence as well as other facial features defining together full facial features, based upon the audio sequence, the features from the neutral face, and the facial features output by the first generator, wherein the latent style variables are to be used to synchronize movement of the full facial features of the visual representation of the face to the spoken words uttered by the speaker; and causing the visual representation of the face to be animated on a display based upon the latent content variables and the latent style variables.