Development of a Cross-Lingual NLP System to Facilitate English Language Learning for Speakers of Low-Resource Languages
Mathusha Sam Lara, B Sreela, K. Sindhu, Vishnu Vandana Devi, Veera Ankalu Vuyyuru, S Prema · 2024
With the connectivity today, the knowledge of English is mostly considered a prime prerequisite for most opportunities, be it education or professional. The proposed system uses the power of advanced natural language processing in order to facilitate communication despite linguistic differences as well as in learning personal and responsive. To mold content into the linguistic sensibilities of the mother tongue of the user, machine translation, sentiment analysis, and contextual awareness are enabled. The system tries to come up with more effective English language learning resources for diverse linguistic communities with the help of high-performance models. That is how the multilingual corpus is curated to represent the diversity of low-resource languages; thus, the learning materials will be relevant and accurate. Language-specific embeddings enable the system to identify and preserve the grammatical structures and expressions unique to each language, thereby making it a smoother transition to English. This adaptive strategy keeps the users motivated and involved in the entire process of learning a new language. Simplicity and accessibility have been designed within this system. Users with different levels of technological literacy can easily use it. The following metrics- improvement in language proficiency, user satisfaction, and engagement levels-will be deployed to appraise this system's effectiveness. Cross-Lingual NLP System One of its major strengths is language understanding at 96.6% accuracy.