AI-Facilitated Mock Interview Systems: An Extensive Review

Abstract 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. Keywords: Artificial Intelligence, Mock Interviews, Emotion Recognition, Natural Language Processing, Speech Analysis, Interview Preparation, Machine Learning

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-10-12
DOI
https://doi.org/10.55041/ijsrem52953
Primary Topic
Robotic Process Automation Applications
Type
article
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article

AI-Facilitated Mock Interview Systems: An Extensive Review

Riya Kevadiya, Kush Patel
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Robotic Process Automation Applications
article

AI-Facilitated Mock Interview Systems: An Extensive Review

Riya Kevadiya, Kush Patel
article en

Abstract

Abstract 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. Keywords: Artificial Intelligence, Mock Interviews, Emotion Recognition, Natural Language Processing, Speech Analysis, Interview Preparation, Machine Learning

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(10)
Openalex Percentile: Top 59%
Robotic Process Automation Applications
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