Abstract:
This project, ”Feedback System for Interview Success using Affective Computing,” is an innovative web application designed to empower interviewees with valuable insights into their emotional responses during job interviews. Leveraging the cuttingedge field of affective computing, the system integrates two powerful components: facial expression analysis and text analysis model. Through real-time video or image analysis, the facial expression analysis model detects and classifies a wide range of expressions displayed by the interviewee. Concurrently, the text analysis model analyzes the interviewee’s textual responses. The user-friendly interface offers an intuitive dashboard that visually represents emotional states and sentiment trends, allowing interviewees to identify moments of confusion, confidence, or neutrality throughout the interview process. It not only contributes to the existing body of knowledge but also presents a practical and accessible tool to enhance interviewees’ self-awareness and interview success. By empowering users with a deeper understanding of their expressions and textual responses, this web application offers a unique opportunity for individuals to grow both personally and professionally. The project’s holistic approach and real-time feedback mechanism redefine interview preparation, transforming it into a more data-driven and self-reflective process. As the project pioneers the fusion of affective computing with interview feedback systems, it holds significant promise in shaping the future of interview evaluations and helping individuals unlock their true potential on the path to career success.
