AI-Based Real-Time Mock Interview System

 Authors:

Aajad Choudhary

Student, Computer Science and Engineering, Parul University, Vadodara

aazadjat5@gmail.com

Abstract:

The increasing competition in the global job market has made interview preparation a critical factor for success. Traditional methods such as practicing with static questions or peer-based mock interviews often fail to provide real-time interaction and personalized feedback. This paper presents an AI-based real-time mock interview system, AirInt, designed to simulate a human-like interview environment using conversational intelligence.

The system integrates speech recognition, natural language processing, and real-time response generation to conduct interactive interview sessions. It dynamically generates questions, analyzes spoken responses, and evaluates both verbal and non-verbal communication aspects. The use of real-time streaming architecture ensures low latency and smooth interaction.Additionally,

The system incorporates facial expression analysis and voice tone analysis to evaluate candidate confidence, emotional state, and communication skills. MongoDB is used for data storage, while Redis maintains short-term conversational context. The system generates detailed performance reports with actionable feedback.

The results demonstrate that the proposed system significantly improves candidate confidence, communication skills, and interview readiness. This research highlights the effectiveness of conversational AI in transforming interview preparation systems.

Keywords: Artificial Intelligence, Mock Interview System, Conversational AI, Real Time Interview Simulation, Speech Recognition, Natural Language Processing, Facial Expression Analysis, Voice Tone Analysis, Machine Learning, Candidate Performance Evaluation