Article Author: Mai Ahmed, Soon-Bok Kwon

This study investigates the application of corpus analysis techniques for the automated assessment of linguistic features in Korean speech, specifically within the context of language disorders associated with cognitive decline. Addressing the limitations of traditional, manual linguistic analysis, this paper proposes a methodology utilizing the corpus morpheme analysis and tagging to quantify semantic and syntactic variables indicative of language disorders. The method details the use of part-of-speech tagging to derive indices related to lexical diversity, semantic coherence, and syntactic complexity, accounting for the unique grammatical characteristics of the Korean language. By automating the analysis of linguistic biomarkers, this approach aims to enhance the precision and efficiency of analyzing and monitoring language disorders in cognitive decline and other language-related pathologies in Korean speakers. While acknowledging the challenges posed by the complexity of Korean morphology, this study concludes that integrating corpus analysis into language pathology research holds significant potential for advancing diagnostic and research methodologies. Future work should focus on validating this approach across various language disorders and developing specialized corpus analysis tools tailored for Korean language pathology assessments.

Keywords: Corpus Analysis; Cognitive Decline; Language Disorders; Speech Analysis

Article Review Status: Published

Pages: 11- 19

Download PDF