Method, electronic device, and computer program product for processing target object

An electronic device, comprising:

• at least one processor;
• and
• a memory coupled to the at least one processor and having instructions stored thereon, wherein the instructions, when executed by the at least one processor, cause the electronic device to perform actions comprising:
• acquiring an initial non-video feature vector on the basis of at least one input of a received speech input and text input;
• taking, in response to not receiving a video input, a default feature vector as an initial video feature vector in place of the video input;
• generating a video feature, a speech feature, and a text feature on the basis of the initial non-video feature vector and the initial video feature vector;
• and
• generating a processing parameter for a target object on the basis of the video feature, the speech feature, and the text feature, wherein the processing parameter includes at least one of an emotion parameter, an attribute parameter, and a pose parameter;
• wherein generating the processing parameter for the target object comprises generating the processing parameter utilizing a trained parameter generator model;
• and
• wherein the parameter generator model is trained over a plurality of iterations of an iterative training process in which the parameter generator model is adjusted based on distances between at least portions of respective distinct training parameter sets obtained in respective different ones of the iterations of the iterative training process.

A computer program product that is tangibly stored on a non-transitory computer-readable medium and comprises machine-executable instructions, wherein the machine-executable instructions, when executed by a machine, cause the machine to perform actions comprising:

• acquiring an initial non-video feature vector on the basis of at least one input of a received speech input and text input;
• taking, in response to not receiving a video input, a default feature vector as an initial video feature vector in place of the video input;
• generating a video feature, a speech feature, and a text feature on the basis of the initial non-video feature vector and the initial video feature vector;
• and
• generating a processing parameter for a target object on the basis of the video feature, the speech feature, and the text feature, wherein the processing parameter includes at least one of an emotion parameter, an attribute parameter, and a pose parameter;
• wherein generating the processing parameter for the target object comprises generating the processing parameter utilizing a trained parameter generator model;
• and
• wherein the parameter generator model is trained over a plurality of iterations of an iterative training process in which the parameter generator model is adjusted based on distances between at least portions of respective distinct training parameter sets obtained in respective different ones of the iterations of the iterative training process.