Research on an AI Interview Evaluation System Integrating Multi-Agent Systems and Virtual Digital Humans

DOI: https://doi.org/10.62517/jbdc.202501408

Author(s)

Jiayi Wu1, Jiaqi Zhang1, Liuyang Gao1, Jialiang Feng1, Bo Meng1, Yifan Wu1, Mingming Gong2

Affiliation(s)

1SArtificial Intelligence and Software Engineering, Henan University of Technology, Zhengzhou, Henan, China 2iFLYTEK COLTD, Hefei, Anhui, China

Abstract

Current AI interview systems face challenges in achieving natural interaction, conducting multidimensional assessments, and ensuring interpretability. This paper proposes and validates an intelligent evaluation framework integrating multi-agent collaboration with 3D virtual digital humans (VDH). The system enables complex question-answering and multidimensional evaluation through the coordinated operation of four functional agents: resume analysis, interview skills, written test training, and job recommendation. Leveraging a 3D Virtual Digital Human interviewer, the system supports multimodal fusion interaction encompassing voice, text, and facial expressions. It automatically generates interview questions, processes multimodal data, and produces multidimensional scoring alongside interpretable feedback reports. Experiments demonstrate that this research significantly enhances the immersion and naturalness of human-machine interaction while strengthening the objectivity, professionalism, and explainability of evaluations. It provides an innovative solution and theoretical foundation for intelligent talent assessment.

Keywords

Multi-agent; Virtual Digital Human; AI Interview; Multimodal Interaction; Comprehensive Evaluation; Explainability

References

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