Voice-Based 2D AI Character Mock Interview Assistant

Abstract: This paper presents Voice-Based 2D AI Character Mock Interview Assistant, an intelligent and animated system for automated interview practice. The system integrates a resume parser, Applicant Tracking System (ATS) scoring, Large Language Model (LLM)-driven question generation, real-time audio dialogue, and a 2D avatar with lip-sync animation, delivering personalized mock interviews with instant feedback. The platform simulates a realistic interview environment where users interact verbally with an AI interviewer capable of generating dynamic, domain-specific questions based on their resumes. Speech recognition and text-to-speech modules enable natural voice communication, while real-time lip synchronization enhances engagement and immersion. The system also includes anti-cheating mechanisms through webcam monitoring to ensure authenticity during sessions. Experimental evaluation demonstrates that the assistant improves users’ communication confidence and response quality through interactive feedback and resume optimization. This project highlights the potential of AI-driven conversational avatars in education, recruitment training, and career development tools.

Keywords: AI-driven mock interview, 2D animated avatar, Applicant Tracking System (ATS), speech recognition, text-to-speech synthesis, natural language processing (NLP), real-time feedback, large language models (LLMs), virtual interview assistant.