This review explores AI-assisted mock interviews, highlighting emotion recognition and natural language processing challenges.
The increasing competitiveness of the job market has increased the need for effective interview preparation tools. This review paper presents trends in AI-assisted mock interview systems that employ emotion recognition, confidence analysis, and natural language processing for comprehensive candidate evaluation. We examine various implementations of such systems, their architectures, approaches, evaluation methods, and shortcomings. The review discovers that while these systems are promising in streamlining interview assessment and providing objective criticism, there are huge problems with accuracy, preventing bias, and ethical considerations. We identify significant research gaps and propose areas for further research in this new field.
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Kevadiya et al. (2025) studied this question.
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