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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM47287
Volume:
9 |
5 |
May 2025
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.
In today’s competitive job market, the performance ability in interviews is essential for the candidates to seek employment. The traditional way of conducting mock interview can be limited by accessibility and personalization. A robust mock interview platform using artificial intelligence will enable candidates to practice in a realistic setting. The aim of our mock interview platform is to bridge this gap which will provide a scalable solution that will enhance the interview preparedness via tailored experiences along with boosting confidence, improving overall performance and catering to diverse industries and job levels. Technology used in this proposed platform will leverage advanced AI algorithms including natural language processing (NLP) and machine learning (ML); which will simulate real interview scenarios can analyse candidates’ responses, offering constructive feedback based on body language, tone and content. By integrating voice recognition and sentiment analysis our platform ensures a compressive evaluation thereby allowing user to refine their interview techniques iteratively. The proposed model comprises an interactive user interface (UI)that will guide the candidates through various interview format such as behavioural and technical questions. User are independent to choice specific industry or roles by receiving a tailored experience which mimics real interviews. The platform Also incorporates inclusively with a feedback loop where the AI generated insides are supplemented with human expertise which will allow user to review their individual performance and refine their skills continuously. This innovative approach will not only boost confidence but will also equip candidates with the tools needed to excel in their job search.
KEYWORDS
Publication Date
5/31/2025
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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No funding information available for this research.
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