Automated Interview Evaluation
The Interview Automation System is an Artificial Intelligence (AI) powered platform designed to help users prepare for real-life interviews. By asking questions and evaluating responses against original answers, our system provides users with a valuable opportunity to practice and improve their inte...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01026.pdf |
| _version_ | 1797658754036006912 |
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| author | Sri Latha Ch. Krishna Kalyan N. Abhilash J. Kaushik O.V.S.N. Balmiki Vinod Venukumar S. |
| author_facet | Sri Latha Ch. Krishna Kalyan N. Abhilash J. Kaushik O.V.S.N. Balmiki Vinod Venukumar S. |
| author_sort | Sri Latha Ch. |
| collection | DOAJ |
| description | The Interview Automation System is an Artificial Intelligence (AI) powered platform designed to help users prepare for real-life interviews. By asking questions and evaluating responses against original answers, our system provides users with a valuable opportunity to practice and improve their interview skills. The research aims to increase users' familiarity with the interview process, ultimately boosting their confidence and improving their chances of success. The workflow of the research involves several key steps, including data pre-processing and database management, audio-based question delivery, and audio-based answer collection and evaluation. Our platform is easily scalable and can be expanded to include additional functionalities such as users confidence detection, resume-based topic questioning, and body language analysis. |
| first_indexed | 2024-03-11T18:03:50Z |
| format | Article |
| id | doaj.art-18972a1e68804425ba1e9e0645ed94da |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-11T18:03:50Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-18972a1e68804425ba1e9e0645ed94da2023-10-17T08:47:19ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014300102610.1051/e3sconf/202343001026e3sconf_icmpc2023_01026Automated Interview EvaluationSri Latha Ch.0Krishna Kalyan N.1Abhilash J.2Kaushik O.V.S.N.3Balmiki Vinod4Venukumar S.5Department of AIMLE, GRIETDepartment of AIMLE, GRIETDepartment of AIMLE, GRIETDepartment of AIMLE, GRIETUttaranchal Institute of Technology, Uttaranchal UniversityKG Reddy College of Engineering & TechnologyThe Interview Automation System is an Artificial Intelligence (AI) powered platform designed to help users prepare for real-life interviews. By asking questions and evaluating responses against original answers, our system provides users with a valuable opportunity to practice and improve their interview skills. The research aims to increase users' familiarity with the interview process, ultimately boosting their confidence and improving their chances of success. The workflow of the research involves several key steps, including data pre-processing and database management, audio-based question delivery, and audio-based answer collection and evaluation. Our platform is easily scalable and can be expanded to include additional functionalities such as users confidence detection, resume-based topic questioning, and body language analysis.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01026.pdf |
| spellingShingle | Sri Latha Ch. Krishna Kalyan N. Abhilash J. Kaushik O.V.S.N. Balmiki Vinod Venukumar S. Automated Interview Evaluation E3S Web of Conferences |
| title | Automated Interview Evaluation |
| title_full | Automated Interview Evaluation |
| title_fullStr | Automated Interview Evaluation |
| title_full_unstemmed | Automated Interview Evaluation |
| title_short | Automated Interview Evaluation |
| title_sort | automated interview evaluation |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01026.pdf |
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