MockMate: AI-Powered Online Mock Interview Assessment and Evaluation System
Dr. Harsha A. Bhute
Dept. of Information Technology
Pimpri Chinchwad College of Eng.
Pune, India
harsha.bhute@pccoepune.org
Aaradhana D. Patil
Dept. of Information Technology
Pimpri Chinchwad College of Eng.
Pune, India
aaradhana.patil21@pccoepune.org
Pooja N. Nemade
Dept. of Information Technology
Pimpri Chinchwad College of Eng.
Pune, India
pooja.nemade21@pccoepune.org
Siddhesh M. Narsingkar
Dept. of Information Technology
Pimpri Chinchwad College of Eng.
Pune, India
siddhesh.narsingkar21@pccoepune.org
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 .
