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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM34616

AI INTERVIEWER

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM34616

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM34616

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MPS

Ms. P. SANDHUSTA

MBASS

Ms. B. A. SRI SWETHA

MSH

MS. S. HEMALATHA

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Abstract

Artificial intelligence (AI) technology has become very important in the recruiting landscape, especially in the automation of the interviews for candidates. At the same time, automation of interviews serves as the gate for recruiting stan- dardization. Despite the standardization attempts through AI automation, recruiting interviews remain bias, unstandardized, and unscalable in the interviews. As such, the automated, AI- based systems remain fundamentally limited to a pre-defined framework where only a limited set of questions and answers are defined. The research designed a new automated intelligent interviewer in the paper titled Dynamic AI Interviewer with Re- sume Analysis. This fully automated intelligent system integrates various AI technologies to efficiently and accurately describe the different phases of an interview with a candidate guided by a current hiring document. It identifies the different skills and experiences in a candidate’s document and creates structured and focused interview questions that are responsive to candidate answers, generating a realistic depth of conversation. As a candidate interview AI system, the system integrates advanced analytics showcasing different sentiments, giving a score towards individual responses, and suggesting mis response areas. The system is designed to demonstrate AI’s potential in creating and fully intergrated interview automation system in a candidates recruiting system. The system is designed for the system to show what AI technology can really do.

KEYWORDS

AI Interviewer Resume Parsing Large Lan- guage Models Real-Time Feedback Conversational AI LLM Integration REST APIs React Node

Cite This Article

Ms. P. SANDHUSTA, Ms. B. A. SRI SWETHA, MS. S. HEMALATHA, "AI INTERVIEWER," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024. https://doi.org/10.55041/IJSREM34616

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Publication Date

12/31/45975

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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