Preparing for job interviews can be challenging for many students and job seekers due to the lack of structured practice platforms and real-time feedback. Traditional mock interview sessions often rely on human evaluators and therefore may lack consistency and accessibility. This research presents an AI-based mock interview web application that integrates artificial intelligence, speech recognition, and facial expression analysis to simulate realistic interview scenarios. The proposed system is developed using React.js for the frontend interface and Node.js with PostgreSQL for backend data management. The application utilizes the Google Gemini API to dynamically generate interview questions tailored to the user's selected job role and experience level. In addition, computer vision techniques implemented using OpenCV and the Haar Cascade classifier enable the system to analyse facial expressions and detect emotional indicators such as confidence and stress during interview responses. The React Speech Recognition Hook allows candidates to respond verbally, creating a more natural and interactive interview experience. By combining AI-generated questions, speech recognition, and real-time emotion analysis, the system provides meaningful feedback that helps candidates improve communication skills, confidence, and overall interview performance.
Artificial Intelligence, Mock Interview System, Facial Expression Recognition, Speech Recognition, Interview Preparation, Computer Vision
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