A Study on the Lexical Richness of Zhongnan Cultural Texts in the Context of Artificial Intelligence Translation
Year: 2025
Type: article
Abstract: This study explores the lexical richness of Zhongnan folk cultural texts translated by artificial intelligence (AI) translation systems. Seven mainstream machine translation (MT) systems were evaluated, including large language models (LLMs) such as ChatGPT-4o, Gemini 1.5 Pro, and iFlytek, and widely-used online translation tools (Google Translate, Baidu Translate, Youdao, and DeepL Translator). Using six specific metrics across two dimensions—lexical density and lexical complexity—this study systematically assesses and compares the English translations of Zhongnan cultural texts generated by these systems. The results reveal distinct lexical features exhibited by different types of MT systems when handling texts embedded with local cultural nuances, offering new empirical evidence for evaluating the lexical competence of AI translation systems. Additionally, this research provides valuable insights for improving the effectiveness of machine translation in cultural dissemination. By examining the lexical perfor-mance of each system, this study identifies key areas for optimizing translation technology and contributes to the broader promotion and global understanding of Zhongnan culture.
Author: Yi Liu
Institution: Northwestern Polytechnical University
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4412503122