Device, method, and program for enhancing output content through iterative generation

A method of improving output content through iterative generation, the method comprising:

• receiving a natural language input;
• obtaining user intention information based on the natural language input by using a natural language understanding (NLU) model;
• setting a target area in base content based on a first user input;
• determining input content based on the user intention information or a second user input;
• generating output content related to the base content based on the input content, the target area, and the user intention information by using a neural network (NN) model;
• generating a caption for the output content by using an image captioning model;
• calculating similarity between text of the natural language input and the generated output content;
• and
• iterating generation of the output content based on the similarity.

A non-transitory computer-readable storage medium comprising instructions which, when executed by at least one processor, causes the at least one processor to:

• receive a natural language input;
• obtain user intention information based on the natural language input by using a natural language understanding (NLU) model;
• set a target area in base content based on a first user input;
• determine input content based on the user intention information or a second user input;
• generate output content related to the base content based on the input content, the target area, and the user intention information by using a neural network (NN) model;
• generate a caption for the output content by using an image captioning model;
• calculate similarity between text of the natural language input and the generated output content;
• and
• iterate generation of the output content based on the similarity.