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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM45858

MockMate: AI-Powered Online Mock Interview Assessment and Evaluation System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM45858

Volume:

9 |

4 |

Apr 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM45858

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.

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Authors

DHAB

Dr. Harsha A. Bhute

ADP

Aaradhana D. Patil

PNN

Pooja N. Nemade

SMN

Siddhesh M. Narsingkar

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Abstract

In the current competitive job market, being well-prepared for interviews is essential to landing a job. Traditional mock interviews, however, are not scalable and can call for a large human resource commitment. By providing a tailored, automated, and interactive online platform driven by artificial intelligence, MockMate tackles this problem. The system mimics actual interview situations, assesses candidate responses in real time, and provides thorough, data-driven feedback by utilizing cutting-edge Natural Language Processing (NLP) and speech-to-text technologies. In addition to customizing their interviews and choosing career roles, candidates can also obtain performance ratings based on their ability to communicate, solve problems, and be technically proficient. The system analyzes the responses using NLP models like BERT, TF-IDF, and Cosine Similarity and records them using OpenAI Whisper. A thorough report that highlights areas for development and compares user responses with ideal answers is produced. Secure, effective, and high-availability service is guaranteed by MockMate, which is built with a scalable architecture utilizing Next.js, Node.js, and PostgreSQL and deployed using Docker and Kubernetes on cloud platforms like AWS/GCP. This platform enables users to increase their interview readiness, boost their confidence, and increase their chances of success by bridging the gap between traditional interview preparation and contemporary AI capabilities.

KEYWORDS

BERT TF-IDF Cosine Similarity OpenAI Whisper Evaluation .

Cite This Article

Dr. Harsha A. Bhute, Aaradhana D. Patil, Pooja N. Nemade, Siddhesh M. Narsingkar, "MockMate: AI-Powered Online Mock Interview Assessment and Evaluation System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 4, Apr 2025. https://doi.org/10.55041/IJSREM45858

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Publication Date

4/28/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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1

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3

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5

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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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