Abstract

Lexical processing plays an important role in language comprehension. After word recognition, necessary knowledge for further language processing, such as word meaning, syntactic category, and usage information, is available. For example, in order to comprehend the structure of a sentence, the syntactic category information of the component word presented in the sentence is necessary. In this paper, we review major issues that have been addressed in Korean word recognition research, and propose a computational model to explain Korean word recognition. The organization of the chapter is as follows: first, we briefly introduce some experimental results in Korean word recognition and morphological processing research. We will focus on studies regarding word frequency, word length, neighborhood effects, form priming, and morphological processing. Second, a computational model for Korean word recognition will be presented. The computational model was proposed to explain the characteristics of Korean morphological representation and processing. However, this computational model can explain other lexical effects such as word frequency, word length, and form priming effects. Third, the simulation results of the computational model will be shown and discussed. We will compare the simulation results with human data to evaluate how well the model simulates Korean word processing and how much the simulated results coincide with that of human processing. We also discuss both the strengths and weaknesses of the computational model.

Linguistic characteristics in Korean lexical processing

A Korean sentence consists of major phrases, which are composed of Eojeols.