ADDRESSING NOISE ISSUES IN SENTENCE STRUCTURE FOR MORPHOLOGICAL ANALYSIS OF ENGLISH LANGUAGE SENTENCES FOR HINDI LANGUAGE USERS
Keywords:
Abstract
Morphological analysis is a fundamental task in natural language processing that involves breaking down words into their constituent morphemes to understand their grammatical structure and meaning. However, when morphological analysis is applied to English language sentences by Hindi language users, noise issues arise due to the syntactic and structural differences between the two languages. This study addresses these noise issues and proposes techniques to improve the accuracy of morphological analysis for English sentences processed by Hindi language users. By exploring methods to handle word order variations, phrasal differences, and other syntactic disparities, this research aims to enhance the effectiveness of morphological analysis tools for bilingual users and facilitate their comprehension of English language sentences.
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