A Comprehensive Survey on Mock Interview Evaluation Systems

—Interviews are essential for evaluating candidates’ skills, knowledge, and suitability for job roles, while mock interviews serve as valuable tools for preparation. With rapid advancements in artificial intelligence (AI) and machine learning (ML), automated interview evaluation has transformed recruitment by offering more objective, efficient, and comprehensive assessments compared to traditional methods. This survey re- views recent AI-driven methodologies for candidate evaluation in mockinter view settings, focusing on multi-modal techniques such as facial emotion recognition, speech analysis, text mining, and nonverbal behavior analysis. It discusses the effectiveness and limitations of various approaches, providing insights into how AI models assess emotional states, speech confidence, personality traits, and knowledge for comprehensive candidate evaluation.

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Publication Details

Journal
International Journal of Advances in Engineering and Management
Published
2024-12-01
DOI
https://doi.org/10.35629/5252-06127174
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

A Comprehensive Survey on Mock Interview Evaluation Systems

Firdouziya M Khadar, Devika G Devika G, Nayana Liz Mathews, Parvathy R Prasad et al.
International Journal of Advances in Engineering and Management
Network Security and Intrusion Detection
article

A Comprehensive Survey on Mock Interview Evaluation Systems

Firdouziya M Khadar, Devika G Devika G, Nayana Liz Mathews, Parvathy R Prasad, Sulaja Sanal
article en

Abstract

—Interviews are essential for evaluating candidates’ skills, knowledge, and suitability for job roles, while mock interviews serve as valuable tools for preparation. With rapid advancements in artificial intelligence (AI) and machine learning (ML), automated interview evaluation has transformed recruitment by offering more objective, efficient, and comprehensive assessments compared to traditional methods. This survey re- views recent AI-driven methodologies for candidate evaluation in mockinter view settings, focusing on multi-modal techniques such as facial emotion recognition, speech analysis, text mining, and nonverbal behavior analysis. It discusses the effectiveness and limitations of various approaches, providing insights into how AI models assess emotional states, speech confidence, personality traits, and knowledge for comprehensive candidate evaluation.

International Journal of Advances in Engineering and ManagementVol. 06(12)
Klinik und Poliklinik für Psychosomatik und Psychotherapie (DE)
Openalex Percentile: Top 74%
Network Security and Intrusion Detection
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