Chinese is a writing system widely used by Chinese people worldwide and has many distinct characteristics. Due to its uniqueness, theories and models of alphabetic languages cannot be directly applied to Chinese. Previous Chinese studies lack systematic computational models for lexical and semantic processing. To address this issue, this study first plans to conduct a systematic review and meta-analysis of previous literature. Next, computational models will be constructed to simulate the processing of Chinese word presented in isolation and during natural reading. The model has the following characteristics: a) it can process both single-character and multi-character words; b) it can simulate orthographic, phonological, and semantic processing of words, as well as their interactions; c) it can simulate the impact of contextual cues on word processing during sentence comprehension. Finally, the assumptions and predictions of the model are planned to be validated in experimental studies. The established model can guide experimental research and has theoretical significance. The research findings will help clarify the cognitive mechanisms of Chinese reading and the dynamic process of lexical processing.

中文是全球华人广泛使用的文字,特点鲜明。由于其特异性,西方语言理论和模型无法直接应用于中文。现有中文词汇加工研究中,缺乏系统的计算模型来模拟词汇语义加工过程。本研究旨在通过计算建模和实验研究方法解决上述问题。研究将系统回顾中文词汇加工已有研究并进行元分析,构建模型以模拟中文词汇在孤立呈现及句子语境中的加工过程。该模型能够加工单字词和多字词,模拟词的形、音、义的加工过程及交互作用,并考虑语境中上下文的影响。最后,通过实验研究验证模型假设。本研究建立的中文词汇语义加工模型有助于理解中文阅读特异性认知机制和词汇加工的动态过程。

国家自然科学基金项目(32371156)