An AI-based framework for improving efficiency and fairness in the interview process
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | An AI-based framework for improving efficiency and fairness in the interview process |
| 2. | Creator | Author's name, affiliation, country | Mohannad Taman; Obeikan Digital Solutions Arab Academy of Science and Technology and Maritime Transport; Egypt |
| 2. | Creator | Author's name, affiliation, country | Yahia Khaled; Banque Misr; Egypt |
| 2. | Creator | Author's name, affiliation, country | Dalia Sobhy; Arab Academy of Science and Technology and Maritime Transport; Egypt |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Artificial intelligence, virtual interviews, Facial emotion recognition, speech processing, Deep learning applications. |
| 4. | Description | Abstract | Artificial intelligence (AI) technologies have advanced to the point where they can help human resource specialists, such as recruiters, by automating major parts of the hiring process and filtering the list of candidates. However, little research has evaluated the use of AI in virtual interviews. This paper presents InstaJob, an AI-powered framework designed to improve efficiency and fairness in the hiring process. It uses deep learning models for face emotion detection, text emotion analysis, and filler word detection in interviews to evaluate candidates’ soft skills, ensuring unbiased assessments. The proposed face emotion detection model achieved a validation accuracy of 77%, which outperforms the other state-of-the-art approaches. Received on, 27 April 2025 Accepted on, 25 May 2025 Published on, 18 June 2025 |
| 5. | Publisher | Organizing agency, location | Arab Academy for Science and Technology and Maritime Transport (AASTMT) |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2025-06-18 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | https://apc.aast.edu/ojs/index.php/ACE/article/view/ACE.2025.05.1.1317 |
| 10. | Identifier | Digital Object Identifier | https://dx.doi.org/10.21622/ACE.2025.05.1.1317 |
| 11. | Source | Title; vol., no. (year) | Advances in Computing and Engineering; Vol 5, No 1 (2025): ACE Volume 5, Issue 1, June 2025 |
| 12. | Language | English=en | en |
| 13. | Relation | Supp. Files |
Latex Folder (5MB) |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
Copyright (c) 2025 Mohannad Taman, Yahia Khaled, Dalia Sobhy https://creativecommons.org/licenses/by-nc/4.0 |