Ancient poetry imagery based on AIGC and Kansei Engineering Research for Visual Translation Strategy

Abstract: Chinese ancient poetry and verse culture has a long history. It not only reflects the unique emotional expression and aspiration of the creators in different historical periods, becoming an artistic presentation of individual emotions and ambitions, but also constructs a cultural symbol and symbolic system with oriental aesthetic characteristics through rich imagery elements. This research uses web crawler technology to collect 360 classic ancient poems and verses, invites experts to form a focus group for text analysis and extract key imagery elements of ancient poetry and verses, and then classifies them into Mountain and Climate, Animal and Plants, Cultural and Artifacts Classes. A 5-level scale questionnaire survey is used to screen out 20 high-frequency imagery elements. Midjourney is used to conduct a pre-experiment on the imagery elements and generate the A version of the element library. After improving the parameters and adding the "cultural anchoring" parameter, the B version of the element library is generated. Subsequently, the emotional words used by the creators in the ancient poetry and verses to express emotions are collected, and the B version of the AIGC-generated images are scored and evaluated through semantic matching using the seven-point semantic differential method. The matching degree between the images and the original text imagery is quantitatively compared by drawing the imagery scale diagram. The AIGC-generated ancient poetry and verse imagery element library through the study of sensuous engineering can convey semantics and emotions that conform to cultural attributes, thereby providing feasible strategies for the visual translation of ancient poetry and verses by AIGC.

Keywords: Kansei Engineering, Ancient poetry imagery, AIGC, Visual Translation

DOI: 10.54941/ahfe1006183

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