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Linguistic Creativity in Generative AI Translation: German Translations of Li Bai’s Poetic Imagery
YU Qinglu, MENG Xiaoguo
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DOI:10.17265/1539-8080/2026.10.003
University of Shanghai for Science and Technology, Shanghai, China
This study examines the linguistic creativity of generative artificial intelligence (AI) in translating poetic imagery, using DeepSeek’s German translations of Li Bai’s poetry as a case study and comparing them with Alfred Forke’s translations. Drawing on the distinction between originality and effectiveness, it analyzes AI-generated translations at the lexical, grammatical, and discourse levels. The findings show that DeepSeek occasionally produces novel lexical choices, unconventional syntactic structures, and rhetorical adaptations. However, these features do not necessarily result in effective literary translation. Misinterpretations of cultural connotations, mismatches in emotional tone, and inappropriate linguistic choices often undermine the poetic meaning and aesthetic effect of the source texts. Compared with Forke’s translations, which demonstrate context-sensitive interpretation and intercultural adaptation, DeepSeek’s apparent creativity relies largely on the recombination of learned linguistic patterns rather than holistic aesthetic judgment. The study argues that AI-generated linguistic novelty should be distinguished from the intentional artistic re-creation characteristic of human literary translation. It concludes that a translator-centered model of human-AI collaboration can use AI to support translation while preserving the human translator’s role in cultural interpretation and aesthetic decision-making.
generative AI, linguistic creativity, poetic imagery, German translation, Li Bai
YU Qinglu & MENG Xiaoguo. Linguistic Creativity in Generative AI Translation: German Translations of Li Bai’s Poetic Imagery. US-China Foreign Language, October 2026, Vol. 24, No. 10, 363-371 10.17265/1539-8080/2026.10.003
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