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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM57169
Volume:
10 |
3 |
Mar 2026
Pages:
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.
This survey examines AI-powered mock interview platforms developed to help students and job seekers improve their interview skills through practical and interactive practice. These systems simulate real interview scenarios, enabling users to rehearse answers, build confidence, and become familiar with the interview process before attending actual interviews. By providing a realistic practice environment, such platforms help users convert academic knowledge into clear and effective communication. The surveyed approaches focus on generating role- specific interview questions by analyzing user-provided CVs and job descriptions, ensuring personalized and relevant practice. User responses are captured using speech recognition and analyzed through Natural Lan- guage Processing and Machine Learning techniques to evaluate grammar, clarity, relevance, and confidence. Instant feedback, along with progress tracking across multiple sessions, helps users identify weak areas and continuously improve their performance. Overall, AI- based mock interview systems contribute significantly to interview readiness, employability, and career develop- ment.
KEYWORDS
Publication Date
10/2/2026
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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