A computer-implemented method for text and audio-based real-time face reenactment, the method comprising: receiving an input text (160, 310) and a target image, the target image including a target face; generating, based on the input text (160, 310), a sequence of sets of acoustic features representing the input text (160, 310); generating, based on the sequence of sets of acoustic features, a sequence of sets of scenario data, the sequence of sets of scenario data indicating modifications of facial key points of a model face for pronouncing the input text (160, 310), wherein the generating the sequence of sets of scenario data includes: generating, based on the sequence of sets of acoustic features, a sequence of sets of mouth key points of the model face by providing the sequence of sets of acoustic features to a first module, the first module being trained to generate, based on a set of acoustic features, a set of mouth key points, the first module being trained based on first images of a first actor speaking first training input texts; and generating, based on the sequence of sets of mouth key points, a sequence of sets of the facial key points of the model face by providing the sets of mouth key points to a second module, the second module being trained to generate, based on the set of mouth key points, a set of the facial key points, the second module being trained based on second images of a second actor speaking second training input texts; generating, based on the sequence of sets of scenario data, a sequence of frames, wherein each of the frames includes the target face modified based on at least one set of scenario data of the sequence of sets of scenario data; and generating, based on the sequence of frames, an output video. receiving an input text (160, 310) and a target image, the target image including a target face; generating, based on the input text (160, 310), a sequence of sets of acoustic features representing the input text (160, 310); generating, based on the sequence of sets of acoustic features, a sequence of sets of scenario data, the sequence of sets of scenario data indicating modifications of facial key points of a model face for pronouncing the input text (160, 310), wherein the generating the sequence of sets of scenario data includes: generating, based on the sequence of sets of acoustic features, a sequence of sets of mouth key points of the model face by providing the sequence of sets of acoustic features to a first module, the first module being trained to generate, based on a set of acoustic features, a set of mouth key points, the first module being trained based on first images of a first actor speaking first training input texts; and generating, based on the sequence of sets of mouth key points, a sequence of sets of the facial key points of the model face by providing the sets of mouth key points to a second module, the second module being trained to generate, based on the set of mouth key points, a set of the facial key points, the second module being trained based on second images of a second actor speaking second training input texts; generating, based on the sequence of sets of acoustic features, a sequence of sets of mouth key points of the model face by providing the sequence of sets of acoustic features to a first module, the first module being trained to generate, based on a set of acoustic features, a set of mouth key points, the first module being trained based on first images of a first actor speaking first training input texts; and generating, based on the sequence of sets of mouth key points, a sequence of sets of the facial key points of the model face by providing the sets of mouth key points to a second module, the second module being trained to generate, based on the set of mouth key points, a set of the facial key points, the second module being trained based on second images of a second actor speaking second training input texts; generating, based on the sequence of sets of scenario data, a sequence of frames, wherein each of the frames includes the target face modified based on at least one set of scenario data of the sequence of sets of scenario data; and generating, based on the sequence of frames, an output video.