Abstract
With the rapid development of natural language processing (NLP) and computer vision technology, the technology of artificial intelligence creative generation (AIGC) has achieved automated conversion from text to video. However, it is still uncertain whether these technologies can provide a deeper understanding of the concept images in Chinese poetries while the videos are generated more efficiently and conveniently. This study analyzes 9 AlGC software based on 8 evaluation dimensions, involving the representative domestic software Aibrm and PIKA with high popularity from aboard. The authors designed a questionnaire survey of the matching rate between poem videos generated by AICG and poem concept images, in terms of Chinese teachers. Also, researchers explore the concretization of abstract concepts in AlGC software. The research found that there are differences in the understanding of concept images of Chinese poetries by different AIGC tools. More than 50% of respondents prefer poetry videos generated by Aibrm, but some believe that both videos do not match poetic concept images. This is mainly due to stiff roles and contexts, insufficient integration, lack of video coherence, and insufficient emotional communication. Despite the development of the AICG, the understanding of poetic concept images should be identified well and improved more. The application of the Chinese poem concept, emotional expression, and cultural integration still requires continuous exploration.
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