This study aims to explore the potential and limitations of ChatGPT in translation, focusing on its application in Neural Machine Translation (NMT).By combining theoretical analysis with empirical research, the study evaluates ChatGPT's strengths and weaknesses.It reveals ChatGPT's superior performance in handling technical documents with high translation quality and efficiency.However, its limitations become evident in addressing cultural nuances and emotional expressions, where semantic deviation or cultural loss often occurs.Moreover, ChatGPT struggles with creative translation, failing to convey the artistic style and emotional depth of original texts, such as literary works and advertisements.The study proposes optimized paths for human-machine collaboration, emphasizing the crucial role of human translators in cultural adaptation and quality assurance.It suggests incorporating multimodal data, dynamic feedback mechanisms, and pragmatic reasoning techniques to enhance machine translation capabilities.The findings conclude that while ChatGPT serves as an efficient translation tool, complex tasks require humanmachine synergy to achieve high-quality cross-cultural communication.
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ZHAO Shujie (2025) studied this question.
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