AI Simulator that Quantifies interview Performance with Real-Time Analytics

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, Issue 4, pp. 64-72, April 2026.

https://doi.org/10.58482/ijersem.v2i4.9

This work is licensed under a Creative Commons Attribution 4.0 International License.

AI Simulator that Quantifies interview Performance with Real-Time Analytics

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E Murali

M Rekha

Kuppam Nithin

Sirisha Pathapati

Madduru Sucharitha

Varalekhari Neeraj Kumar

1Professor, Department of CSE, Siddharth Institute of Engineering & Technology, Puttur, AP, India.

2Assistant Professor, Department of CSE, Siddharth Institute of Engineering & Technology, Puttur, AP, India.

3-5UG Scholar, Department of CSE, Siddharth Institute of Engineering & Technology, Puttur, AP, India.

Abstract: Traditional interview preparation often fails to ad- dress the critical role of non-verbal communication, leaving candidates unaware of how their confidence and emotional state are perceived. To bridge this gap,  this method presents an AI-driven mock interview simulator that provides a holistic evaluation of a candidate’s performance. The system leverages a multi- modal AI pipeline to analyze a confluence of verbal and non- verbal cues. Key modalities include facial expression analysis for emotional sentiment, vocal tonality assessment for confidence markers such as pitch and pace, and linguistic pattern analysis of the transcribed speech to measure clarity and identify filler word usage. The platform delivers a tailored experience by generating personalized interview questions and culminates in a comprehensive performance report. This report presents users with quantitative metrics and actionable insights, pinpointing specific emotional cues and highlighting concrete areas for development. By providing a safe, data-driven environment for practice, this tool empowers candidates to master the crucial soft skills required to succeed, thereby enhancing their confidence and competitiveness in the modern job market.

Keywords: Multi-model AI Pipeline, Mock Interview Simulator, Real-Time Feedback, Facial Emotion Recognition, Vocal Tone Analysis.

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This article is part of Volume 2, Issue 4 (April 2026)