Intelligent Generation of New Media Art Based on User Experience Design

Abstract

New media art (NMA) usually requires users of interaction and participation, and users expect to get real-time feedback in the process of their participation. This paper proposes using sensors to collect the data generated in the process of user experience in real time combined with internal data mining and the deep-learning model,GAN, to evaluate and obtain the standard data set as prompt transmitted to AIGC for real-time generated content. The design team uses the AIGC technology to reorganize and continuously optimize the model to get a new media art that meets the needs of the user experience. This method can help artists to avoid the exhaustion of inspiration. And to help enterprises quickly produce different new media art works with different characteristics, so as to improve the penetration rate of new media art in the society.