Simplified Chinese lexicon project: A lexical decision database with 8105 characters and 4864 pseudocharacters.

Area of Science:

• Cognitive Psychology
• Psycholinguistics
• Computational Linguistics

Background:

• Existing Chinese character datasets lack comprehensive coverage.
• Understanding visual processing of Chinese characters is crucial.

Purpose of the Study:

• To create a comprehensive lexical dataset for simplified Chinese characters and pseudocharacters.
• To investigate the influence of character attributes on visual processing.
• To provide resources for behavioral experiments and statistical modeling.

Main Methods:

• Collected lexical decision data for 8105 standard and 4864 pseudocharacters.
• Developed a novel method for generating pseudocharacters based on character hierarchy.
• Conducted virtual experiments on visual complexity, neighborhood size, and regularity.

Main Results:

• Newly collected data demonstrated comparable reliability to existing megastudies.
• Higher visual complexity increased recognition difficulty.
• Regular characters showed longer processing times with small neighborhood sizes.
• Identified a three-way interaction between character frequency, radical frequency, and residual component frequency.
• Radical and residual component frequency interactions modulated pseudocharacter rejection.

Conclusions:

• The SCLP offers a valuable, comprehensive resource for Chinese character research.
• Character attributes significantly impact visual processing and recognition.
• The findings advance our understanding of lexical processing in Chinese.