Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM24451

Automated Video Interviews Using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM24451

Volume:

7 |

7 |

Jul 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

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.

Share this article:

Authors

YA

Yash Agarwall

SP

Shubham Pamecha

SB

Shreyansh Bansal

APRK

Asst. Prof. Rashmi K.B

Author Services & Downloads

Full Articles

Abstract

After the pandemic, Every sector has experienced the impact of change. corona. Many people are unemployed and soon we will see how the world needs more job seekers. Since there is no such process where you can conduct interviews and screening, you must be ready to engage in the recruitment process with IT solutions. Now we have voice recorders or skype phone alerts that are not yet undergone feature analysis. So, overcoming all these shortcomings and introducing a new era of the interview process is the main goal of the project. With artificial intelligence systems, we can predict human skills and recommended types of work, as AI will be introduced in today’s industry, namely recruitment agencies. By utilizing a range of machine learning algorithms, including the convolutional neural network, Naive Bayes, Random Forest, and SVM, significant progress can be made.. Employee sentiment, voice to text, face to face company verification process will be implemented in this project. In the future, the system can access user logs that can analyze the effectiveness and efficiency of users. Also, employees are able to get benefit from this system by analyzing their emotions and personality, we can see such a system in future interviews.

KEYWORDS

Naïve bayes random forest SVM convolutional neural network (CNN) TensorFlow emotion company verification resume parsing image processing

Cite This Article

Yash Agarwall, Shubham Pamecha, Shreyansh Bansal, Asst. Prof. Rashmi K.B, "Automated Video Interviews Using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 7, Jul 2023.

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

8/6/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

1

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

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

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...