Fluent Futures: Cutting-Edge AI Techniques for Mastering English
B. Lavanya, R. Subhashini, Riyaz Mohammad, K S Punithaasree, K. Chandra Sekhar, P. Nagaraj · 2024
Cutting-Edge AI Techniques for Mastering English provides a new approach to tailored feedback in English learning that has been considerably enhanced by sophisticated AI techniques. This study provides a unique strategy to generate individualized feedback utilizing BERT (Bidirectional Encoder Representations from Transformers) and a sequence-to-sequence fine-tuning mechanism. This technique uses the ELLIPSE Corpus, a huge dataset of English Language Learner (ELL) writing samples tagged with proficiency scores and thorough comments, to deliver individualized corrections and explanations. The sequence-to-sequence approach is fine-tuned to map learner input to precise feedback, addressing components of language competency such as grammar, vocabulary, and syntax. BERT's extensive contextual awareness makes it easier to identify complex mistakes and generate appropriate repairs and explanations. Personalized feedback is strengthened by tailoring it to particular learner profiles and updating it in response to student interactions and progress. The feedback's efficacy is measured using measures like as student satisfaction, gains in writing skill, and alignment with ELLIPSE Corpus proficiency results. This technique promises to provide exact, actionable, and adaptable feedback, so considerably enhancing the language learning experience and assisting learners in meeting their competence objectives. The experimental findings show that ROUGE 1 is 0.761428, ROUGE 2 is 0.65428, and ROUGE L is 0.761428, indicating the success of the suggested technique.