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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65097
Volume:
10 |
6 |
Jun 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Information Technology
RMD Sinhgad School Of Engineering
Information Technology
RMD Sinhgad School Of Engineering
Information Technology
RMD Sinhgad School Of Engineering
Information Technology
RMD Sinhgad School Of Engineering
Information Technology
RMD Sinhgad School Of Engineering
The Artificial Intelligence (AI) Mock Interview Platform is an advanced system designed to enhance interview preparation through intelligent automation and real-time performance analysis. Building upon the initial prototype, the system integrates Natural Language Processing (NLP), Computer Vision, and Speech Analysis to simulate realistic interview scenarios and evaluate candidate performance effectively.The platform incorporates face detection and verification using the Haar Cascade algorithm to ensure secure and efficient user authentication. It conducts domain-specific and HR interviews in both text and voice modes, analyzing responses based on multiple parameters such as accuracy, fluency, sentiment, and confidence. Additionally, basic facial analysis is performed to monitor user engagement during the interview process.The system generates detailed feedback reports and performance scores, helping users identify strengths and areas for improvement. The enhanced design focuses on simplicity, faster execution, and accessibility while maintaining reliable evaluation. Experimental observations indicate that the platform improves user confidence and interview readiness.This solution provides a cost-effective and accessible approach to interview preparation, reducing dependency on human interviewers while delivering consistent and data-driven feedback.
KEYWORDS
The AI Mock Interview Platform provides an efficient, interactive, and intelligent solution for preparing candidates for real-world interviews. By leveraging Artificial Intelligence techniques such as Natural Language Processing (NLP), Speech Analysis, and Haar Cascade-based face detection, the system evaluates user performance in terms of communication skills, confidence, and overall behavior.The platform enables users to identify their strengths and weaknesses through structured feedback and performance reports, helping them improve both technical and soft skills. Its automated and accessible nature reduces dependency on human interviewers while ensuring consistent and objective evaluation.Overall, the system enhances interview readiness, builds user confidence, and bridges the gap between theoretical preparation and practical performance. The proposed solution demonstrates the potential of AI-driven systems in transforming interview preparation into a more effective and scalable process.
1. Mrs. Navya S Rai1, Abhiram K R2, Adithya P3 , Hrithik N R4 ,” AI Based Interview Evaluator: An Emotion and Confidence Classifier”, Published year - 4, April 2024. 2. DulminiYashodha Dissanayake1, Venuri Amalya2, Raveen Dissanayaka3, Lahiru Lakshan4, Pradeepa Samarasinghe5, Madhuka Nadeeshani6, Prasad Samarasinghe,” AI-based Behavioural Analyser for Interviews/Viva”, Published Year- 07 February 2023. 3. B Y Kim, B C Lee,” DEVELOPMENT OF AN AI-BASED INTERVIEW SYSTEM FOR REMOTE HIRING”, published Year- 11 January 2022. 4. Noor Fadzilah Ab Rahman1, Shir Li Wang2*, Nurkaliza Khalid3,” ENSEMBLE LEARNING IN EDUCATIONAL DATA ANALYSIS FOR IMPROVED PREDICTION OF STUDENT PERFORMANCE: A LITERATURE REVIEW”, Published Year- 24 (March 2025). 5. Prof.Taware. R.K*1, BhagyashreeShinde*2, Nikita Rasal*3, SnehalGhorpade*4,” MART INTERVIEW SYSTEM USING AI TECHNOLOGY”, published year- 02/February-2024. 6. HarshalGunjal*1, Sachin Tathe*2,” ARTIFICIAL INTELLIGENCE BASED INTERVIEW SYSTEM: A REVIEW”, published year- 04/April-2025.
Publication Date
6/17/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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