Generative AI and Classical Chinese Moon Imagery in Translation
DOI:
https://doi.org/10.54097/advtk584Keywords:
Generative AI, classical Chinese poetry, moon imagery, literary translation, error-aware evaluationAbstract
Generative artificial intelligence has created new possibilities for literary translation and for the international circulation of classical Chinese poetry. However, AI translation becomes problematic when poetic meaning depends on culturally dense imagery rather than direct explanation. This paper investigates how generative AI reconstructs the moon image in English translation, using Chat GPT and ERNIE Bot as two representative systems. A small experimental dataset of six classical moon-image cases is constructed, and four evaluation indicators are used: literal accuracy, cultural retention, aesthetic quality, and over-explanation risk. The results show that both systems perform strongly in literal accuracy but less consistently in cultural retention and aesthetic quality. They also tend to replace poetic ambiguity with explicit emotional explanation. The paper concludes that generative AI is useful for first-level comprehension and comparative translation practice, but human revision remains necessary for cultural judgment and aesthetic control.
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