AI-Interview Performance Analyzer Using Python

Abstract: In today's recruitment process, fairly and consistently evaluating interview performance remains a significant challenge due to human bias. To tackle this, the project introduces an AI-Interview Performance Analyzer.a webbased intelligent system that evaluates candidates through aptitude tests and live interview analysis. The system administers timed, multi-level aptitude tests and records live interviews using webcam technology. AI-driven scoring algorithms assess both the aptitude test results and the interview performance to produce a comprehensive evaluation score. The application ensures secure access with OTP-based password recovery and provides role-specific dashboards for both candidates and administrators. Administrators can efficiently manage users, aptitude questions, interview recordings, and result reports. The system is built using HTML, CSS, and JavaScript for the frontend, Python (Flask) for the backend, and MySQL for data storage. This solution enhances the accuracy, transparency, and efficiency of the recruitment process by offering a fair and automated method of evaluating interviews. Recruitment interviews frequently rely on human judgment, which can result in bias and uneven assessments. The AI-Interview Performance Analyzer is a web-based tool designed to automate and streamline the interview evaluation process. It assesses candidates through aptitude tests and recorded live interviews. These aptitude tests are timed and consist of multiple levels, while interviews are conducted using webcam technology. AI-driven scoring methods evaluate both the aptitude test results and interview performance to calculate a total score and determine the candidate's selection status. The system features secure login, OTP-based password recovery, and distinct dashboards for users and administrators. This tool assists recruiters in making fair and precise hiring decisions. keywords: AI Interview Analyzer, Aptitude Test, Performance Evaluation, Flask, MySQL, Recruitment System, Web Application