Authors: Mr.Santosh Handignoor, Mr.Himanshu Singh, Prof. Vaishali Suryawanshi, Prof. Dipak Kadve
Abstract: Interview readiness is a decisive factor in determining employability and professional advancement; however, a large number of students struggle to perform effectively due to limited practice opportunities, anxiety, and the absence of structured, objective feedback. Recent developments in Artificial Intelligence (AI) have enabled the creation of intelligent systems capable of simulating interview scenarios and evaluating candidates in a consistent and data-driven manner. This research examines an AI-based mock interview framework that utilizes Natural Language Processing for response evaluation, speech analytics for assessing confidence and fluency, and facial expression analysis for understanding non-verbal behavior. By combining these AI techniques, the system delivers personalized feedback that highlights communication gaps, confidence issues, and knowledge deficiencies. Unlike traditional mock interviews, the proposed approach allows repeated practice without dependency on human evaluators, ensuring scalability and fairness. The study is supported by quantitative analysis conducted on a student dataset, revealing notable improvements in interview performance, self-confidence, and communication effectiveness after exposure to AI-driven mock interviews. The results demonstrate that AI-based interview preparation tools can significantly enhance interview readiness and serve as an effective alternative to conventional training methods. This work reinforces the growing role of AI in employability skill development and its potential to transform interview preparation practices in academic and recruitment environments.
DOI: https://doi.org/10.5281/zenodo.18387039
