Обнаружение англо-русских лексически родственных слов с использованием NLP машинного обучения и языка Питон (English/Russian lexical cognates detection using NLP Machine Learning with Python)
Аннотация
Language learning is a remarkable endeavor that expands our horizons and allows us to connect with diverse cultures and people around the world. Traditionally, language education has relied on conventional methods such as textbooks, vocabulary drills, and language exchanges. However, with the advent of machine learning, a new era has dawned upon language instruction, offering innovative and efficient ways to accelerate language acquisition. One intriguing application of machine learning in language learning is the utilization of cognates, words that share similar meanings and spellings across different languages.
To address this subject, this research paper proposes to facilitate the process of acquiring a second language with the help of artificial intelligence, particularly neural networks, which can identify and use words that are similar or identical in both the learner's first language and the target language,
These words, known as lexical cognates which can facilitate language learning by providing a familiar point of reference for the learner and enabling them to associate new vocabulary with words they already know.
By leveraging the power of neural networks to detect and utilize these cognates, learners will be able to accelerate their progress in acquiring a second language.
Although the study of semantic similarity across different languages is not a new topic, our objective is to adopt a different approach for identifying Russian-English Lexical cognates and present the obtained results as a language learning tool, by using the lexical and semantic similarity data sample across languages to build a lexical cognates detection and words association model.
Subsequently, depend on our analysis and results, will present a word association application that can be utilized by end users.
Given that Russian and English are among the most widely spoken languages globally and that Russia is a popular destination for international students from around the world, it served as a significant motivation to develop an AI tool to assist individuals learning Russian as English speakers or learning English as Russian speakers.
To address this subject, this research paper proposes to facilitate the process of acquiring a second language with the help of artificial intelligence, particularly neural networks, which can identify and use words that are similar or identical in both the learner's first language and the target language,
These words, known as lexical cognates which can facilitate language learning by providing a familiar point of reference for the learner and enabling them to associate new vocabulary with words they already know.
By leveraging the power of neural networks to detect and utilize these cognates, learners will be able to accelerate their progress in acquiring a second language.
Although the study of semantic similarity across different languages is not a new topic, our objective is to adopt a different approach for identifying Russian-English Lexical cognates and present the obtained results as a language learning tool, by using the lexical and semantic similarity data sample across languages to build a lexical cognates detection and words association model.
Subsequently, depend on our analysis and results, will present a word association application that can be utilized by end users.
Given that Russian and English are among the most widely spoken languages globally and that Russia is a popular destination for international students from around the world, it served as a significant motivation to develop an AI tool to assist individuals learning Russian as English speakers or learning English as Russian speakers.