Video generation model training

An apparatus for video generation model training, comprising:

• processing circuitry configured to:
• obtain at least two first sample pairs, each of the first sample pairs including a first sample speech segment and a first sample video segment corresponding to the first sample speech segment, the first sample video segment of each of the first sample pairs including images of a respective virtual object, and a facial expression of the virtual object in the first sample video segment of each of the first sample pairs matching speech content of the first sample speech segment of the corresponding one of the first sample pairs;
• generate, through a video generation model based on the first sample speech segment of each of the first sample pairs, a respective predicted video segment corresponding to the first sample speech segment of each of the first sample pairs;
• and
• train the video generation model based on the predicted video segment and the first sample video segment corresponding to the first sample speech segment of each of the first sample pairs.

A non-transitory computer-readable storage medium storing instructions, which when executed by a processor, cause the processor to perform a method for video generation model training, the method comprising:

• obtaining at least two first sample pairs, each of the first sample pairs including a first sample speech segment and a first sample video segment corresponding to the first sample speech segment, the first sample video segment of each of the first sample pairs including images of a respective virtual object, and a facial expression of the virtual object in the first sample video segment of each of the first sample pairs matching speech content of the first sample speech segment of the corresponding one of the first sample pairs;
• generating, through a video generation model based on the first sample speech segment of each of the first sample pairs, a respective predicted video segment corresponding to the first sample speech segment of each of the first sample pairs;
• and
• training the video generation model based on the predicted video segment and the first sample video segment corresponding to the first sample speech segment of each of the first sample pairs.