"COMPARATIVE ANALYSIS OF VERB ASPECTS IN ENGLISH, KOREAN, AND UZBEK USING NLP TOOLS"

Abstract

This paper explores the systems of aspect of the verb in the English, Korean, and Uzbek languages within the framework of Natural Language Processing. The verb aspect serves as an important linguistic feature and translates into essential component in machine translation. In contrast to English that employs auxiliary verbs and periphrastic constructions to express aspects, Korean and Uzbek use morphological markers. This paper describes the implementation of many advanced techniques of NLP, such as POS tagging, dependency parsing, and classification based on machine learning algorithms, for studying representation of aspect in these languages. The comparison reveals both common tendencies and divergencies of the languages, pointing out the scope of the processing for different languages with different linguistics structures. The scope of this work is in cross-linguistics NLP whereas raises the prospects for further development of aspect detection systems for languages with scarce resources.