Abstract: An innovative initiative at the nexus of cutting-edge technology and human skill development is the AI Based Interview Evaluator: An Emotion and Confidence Classifier. This initiative, which aims to transform interview preparation methods, makes advantage of state-of-the-art AI capabilities by putting affective computing to use as an evaluator and interviewer. The technology surpasses conventional techniques by integrating speech-based emotion detection and facial expression analysis, providing aspiring professionals with an engaging learning environment. Driven by the necessity to tackle the inadequacies of traditional interview preparation, the project seeks to offer users individualized question development, adaptive learning, and real-time feedback. The system offers a holistic approach to interview skill including modules for facial and speech-based emotion detection, chatbot functionality, and interface with NLP and LSTM networks. The system promises a comprehensive approach to interview skill enhancement. Although the project offers benefits like instantaneous feedback and adaptability to other domains, it also recognizes issues with data dependency, context understanding, and ethical considerations. All things considered, the AI Interview Evaluator aims to reinvent interview preparation by giving users a priceless tool for refining their abilities and increasing their self-assurance in actual interview situations.

Keywords: AI Based Interview Evaluator, AI interview, Facial Expression Analysis, Deep Face, Machine Learning, Convolution Neural Network, Speech-based Confidence Detection, Librosa, Random forest algorithm.

| DOI: 10.17148/IARJSET.2024.11442