While extensive research has focused on ChatGPT in recent years, very few studies have systematically quantified and compared linguistic features between human-written and Artificial Intelligence (AI)-generated language. This study aims to investigate how various linguistic components are represented in both types of texts, assessing the ability of AI to emulate human writing. Using human-authored essays as a benchmark, we prompted ChatGPT to generate essays of equivalent length. These texts were analyzed using Open Brain AI, an online computational tool, to extract measures of phonological, morphological, syntactic, and lexical constituents. Despite AI-generated texts appearing to mimic human speech, the results revealed significant differences across multiple linguistic features such as consonants, word stress, nouns, verbs, pronouns, direct objects, prepositional modifiers, and use of difficult words among others. These findings underscore the importance of integrating automated tools for efficient language assessment, reducing time and effort in data analysis. Moreover, they emphasize the necessity for enhanced training methodologies to improve the capacity of AI for producing more human-like text.

翻译：尽管近年来大量研究聚焦于ChatGPT，但极少有研究系统性地量化并比较人工撰写文本与人工智能生成语言之间的语言特征。本研究旨在探究各类语言成分在两种文本中的表征方式，评估AI模仿人类写作的能力。以人工撰写的论文作为基准，我们提示ChatGPT生成长度相当的论文。使用在线计算工具Open Brain AI对这些文本进行分析，以提取音系、形态、句法和词汇成分的度量指标。尽管AI生成文本看似模仿人类语言，但结果显示其在辅音、词重音、名词、动词、代词、直接宾语、介词修饰语以及难词使用等多个语言特征上存在显著差异。这些发现凸显了整合自动化工具以提升语言评估效率、减少数据分析时间与精力的重要性。此外，研究结果也强调了需要改进训练方法以增强AI生成更类人文本的能力。