%0 Journal Article %1 noauthororeditor %A Priscila, Steffi. R | S. Suman Rajest | R. Regin | Shynu T | S. Silvia %D 2023 %J CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE %K (CNN), Convolution Emotion Eye Eye-gaze HR Network Neural Recognition blink interview, rate, tracking, %N 6 %P 78-102 %T Analysis of an Interview Based on Emotion Detection Using Convolutional Neural Networks %U https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1209/1272 %V 4 %X Interviewing potential employees is an essential component of the employment process. Many people have difficulty progressing through the one-on-one interview sessions, despite having performed exceptionally well in the earlier rounds of the competition. The very reason for this is that people do not conduct enough self-analysis on the facial expressions and degrees of confidence they project during interviews. The candidates' technical, verbal, and logical skills are evaluated in a series of mock interviews; however, there are not enough resources available to help the candidates prepare for the actual face-to-face interviews. Using Convolution Neural Networks (CNN), the goal is to recognise and analyse the emotions that are being expressed by the candidates in order to determine the level of confidence that a person has. The computation of eye blink rate to detect anxiety and eye gaze tracking to detect distraction are both utilised in this study so that the accuracy of the results can be improved. The results are then compiled and delivered to the candidate in the form of a report. This provides the interview candidates with valuable information that can effectively assist them in preparing for their one-on-one interviews.

@article{noauthororeditor, abstract = {Interviewing potential employees is an essential component of the employment process. Many people have difficulty progressing through the one-on-one interview sessions, despite having performed exceptionally well in the earlier rounds of the competition. The very reason for this is that people do not conduct enough self-analysis on the facial expressions and degrees of confidence they project during interviews. The candidates' technical, verbal, and logical skills are evaluated in a series of mock interviews; however, there are not enough resources available to help the candidates prepare for the actual face-to-face interviews. Using Convolution Neural Networks (CNN), the goal is to recognise and analyse the emotions that are being expressed by the candidates in order to determine the level of confidence that a person has. The computation of eye blink rate to detect anxiety and eye gaze tracking to detect distraction are both utilised in this study so that the accuracy of the results can be improved. The results are then compiled and delivered to the candidate in the form of a report. This provides the interview candidates with valuable information that can effectively assist them in preparing for their one-on-one interviews.}, added-at = {2023-09-23T11:24:49.000+0200}, author = {Priscila, Steffi. R | S. Suman Rajest | R. Regin | Shynu T | S. Silvia}, biburl = {https://www.bibsonomy.org/bibtex/24837e66fbafec39dfd909409ad109a34/centralasian_20}, interhash = {16eb7d61d49ca14f76b5457749ab8665}, intrahash = {4837e66fbafec39dfd909409ad109a34}, issn = {2660-5317}, journal = {CENTRAL ASIAN JOURNAL OF THEORETICAL AND APPLIED SCIENCE}, keywords = {(CNN), Convolution Emotion Eye Eye-gaze HR Network Neural Recognition blink interview, rate, tracking,}, language = {english}, month = may, number = 6, pages = {78-102}, timestamp = {2023-09-23T11:24:49.000+0200}, title = {Analysis of an Interview Based on Emotion Detection Using Convolutional Neural Networks}, url = {https://cajotas.centralasianstudies.org/index.php/CAJOTAS/article/view/1209/1272}, volume = 4, year = 2023 }