통사적 복잡도 자동 계산 프로그램 개발 연구
Development of an Automatic Syntactic Complexity Analyzer for Korean
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Recent advancements in deep learning and the expansion of large-scale Korean corpora have highlighted a pressing need for specialized analytical tools in Korean linguistics and education. This study addresses this gap by developing an automatic syntactic complexity analyzer. Our approach adapts the syntactic complexity framework proposed by Na(2025), partially modifying the framework of Seo et al.(2013), and employs a rule-based mechanism to analyze basic sentence structures, modifiers, embedded structures, and coordinate structures. To enhance the precision of these rules, we integrated the morphological analyzer and dependency parser developed by ETRI(2024). Given the significance of syntactic complexity as an index and the current scarcity of automatic syntactic complexity analyzers for Korean, this study offers a meaningful contribution to the field.
Abstract
Recent advancements in deep learning and the expansion of large-scale Korean corpora have highlighted a pressing need for specialized analytical tools in Korean linguistics and education. This study addresses this gap by developing an automatic syntactic complexity analyzer. Our approach adapts the syntactic complexity framework proposed by Na(2025), partially modifying the framework of Seo et al.(2013), and employs a rule-based mechanism to analyze basic sentence structures, modifiers, embedded structures, and coordinate structures. To enhance the precision of these rules, we integrated the morphological analyzer and dependency parser developed by ETRI(2024). Given the significance of syntactic complexity as an index and the current scarcity of automatic syntactic complexity analyzers for Korean, this study offers a meaningful contribution to the field.