Developing a Generative AI Interview Skills Training System for Individuals with Disabilities

Abstract

This study proposes a Generative Artificial Intelligence (GenAI) interview skills training system aimed at enhancing the employability of individuals with disabilities through improved interview skills. Compared to traditional methods such as mixed-reality simulations and robotic role-playing, this system offers enhanced personalization, realism, and adaptability. The system features 11 job-specific scenarios and three difficulty levels with adaptive feedback, enabling personalized and progressive skill development. In addition, an intuitive interface displays virtual interviewer prompts alongside real-time visual feedback, helping users refine both their verbal and non-verbal communication skills such as facial expressions, gestures, and posture. A major advantage of this system lies in its real-time feedback mechanism, which addresses individual training needs while reducing reliance on human trainers. This work demonstrates the potential of AI-driven simulation to support accessible, personalized vocational training. Future research will focus on optimizing the AI feedback engine, extending the system's applicability across disability types, and evaluating its long-term impact on employment outcomes.

Ähnliche Arbeiten