Intelligent Question Generator System using Natural Language Processing

Question generation system in most educational institutes is not automated. There are various methods in which objective and subjective question generation is existing, but not those algorithms are not very accurate. Automation of question generation systems can assist learners to discover the levels of their expertise and increase their knowledge by helping them in clarifying their queries. It can also be widely used in various other fields such as for placement activities. In this paper, the proposed model main objective is to design and implement an automated question generator using Natural Language Processing(NLP) techniques. The proposed system will use T5 transformer and Bidirectional Encoder Representations from Transformers (BERT) technique. The performance of the automated question generator is evaluated using accuracy, relevance, and fluency of the generated questions. The results of the system will Incorporate user feedback to improve the performance and effectiveness of the question generator.