A Review on Adaptive interview preparation system

Abstract

Traditional interview preparation methods often lack personalization and fail to provide dynamic, real -time response for effective skill development. This paper reviews the basic technologies required to develop an adaptive interview prep bot, which is a versatile platform designed to simulate realistic interview scenarios. The proposed system integrates several major AI-operated modules: a re-introduction to generate sewn questions, an adaptive engine for dynamic text-based Q and A, an integrated growth environment with an autograph for real-time code evaluation, an integrated growth environments, and the basic feeling to detect the basic feeling to offer feedback on soft skills. By synthesizing research from areas of natural lan- guage processing (NLP), affectionate computing, and automated code analysis, this review underscores a harmonious outline for creating an intelligent, end-to-end interview practice tool. The resulting platform aims to provide candidates with a strong, accessible and personal solution to significantly increase their interview readiness.