ADDITIONAL NEW MATHEMATICAL MODELS OF VERB PHRASEOLOGY FOR COMPUTER TRANSLATION FROM ENGLISH TO UZBEK

Abstract

It is well known that the process of any computer translation system involves encoding the meaning of the input text in a natural language and re-encoding this meaning in the target language while maintaining semantic consistency with the source text. One approach to achieving this goal is the formalization of the grammatical structures of the natural languages involved in translation systems. More precisely, grammatical structures are based on linguistic rules that determine word structures and their classification according to parts of speech. Analyzing word structures enables the construction of logically sound mathematical models. This article examines how verbs in English and Uzbek form syntactic relationships and how verb categories are classified during the computer translation process. The study analyzes the key aspects of a morpho-analyzer that ensures accurate and meaningful automatic translation. Additionally, it classifies verb-related words and verb-forming affixes in both languages, along with their patterns and mathematical models.