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An Automated Online Mock Interview System Using Machine Learning and Emotion Analysis

S. SHIRLEY., M.C.A., (Ph.D)

(Assistant Professor, Department of Master of Computer Applications)

M. NIVEDHA., MCA

Christ College of Engineering and Technology

Moolakulam, Oulgaret Municipality, Puducherry – 605010

ABSTRACT

Interview preparation is a crucial aspect of career development for students and job seekers; however, access to realistic and personalized interview practice remains limited. Traditional mock interview methods rely heavily on human evaluators, making them time-consuming, costly, and difficult to scale. This paper presents an Online Mock Interview System using Machine Learning that provides an automated and intelligent interview preparation platform. The system analyzes uploaded resumes to extract technical skills using Natural Language Processing techniques and generates skill-based interview questions dynamically. Candidates respond to questions within a fixed time while their audio and video responses are recorded. Facial emotions are analyzed using a Convolutional Neural Network, and spoken answers are evaluated using speech-to-text conversion and similarity matching algorithms. The system produces an automated score and detailed feedback, enabling candidates to assess both technical knowledge and behavioral performance. The proposed approach reduces dependency on manual interviewers and offers an effective, unbiased, and scalable solution for interview preparation.

KEYWORDS

Online Mock Interview System, Machine Learning, Resume Parsing, Skill Extraction, Facial Emotion Recognition, Speech Recognition, Natural Language Processing, Convolutional Neural Network, Automated Interview Evaluation, Artificial Intelligence