Enhancing Virtual Hiring Through AI-Driven Fake LipSync Detection and Career Chatbot

The paper introduces an integrated solution that can take care of two of the biggest challenges in the hiring game these days: guaranteeing that video interviews are real, i.e. interactions from a solid candidate, and providing personalized support, such as through an AI chatbot, particularly career-driven. The changing nature of the hiring process to a remote mechanism makes it critical for each candidate to experience this commitment and engagement at the same time as enhancing their experience.The specific point is the detection of Fake LipSync and Expression Tracking, which are used in conjunction with advanced technologies like AWS Rekognition for facial analysis and Wav2Vec2 for speech-to-text analysis. The system looks at the audio-video synchronization in the stored video interviews to point out differences in the spoken voices and lip movements, highlighting possible alterations or manufabricated behaviours. Along with that, there will also be an analysis of various expressions made to give recruiters some background into predisposition, honesty, and necessarily good interpersonal qualities of a potential candidate by dealing with facial landmarks and current lip mismatches of the snapshot performances.The second component, an AI-empowered Career Chatbot, processes the LLaMA language model with an integration that occurs with LangChain in order to enhance document retrieval and provide a real understanding of context. The chatbot learns with the recruitment specific domain which suggestions about jobs will suit someone the most while accommodating him to answer very frequently asked questions and giving information to prepare for interviews. Using the aim of embedding and retrieving information from relevant documents at the right time, the interaction will become more precise, contextual, yet highly improved within the candidate experience on the recruitment platforms.