Automated Training for Job Interviews

© 2020 by IJCTT Journal
Volume-68 Issue-3
Year of Publication : 2020
Authors : Rochelle Cordeiro, Anol Kurian, Brinel D`souza, Brijmohan Daga
DOI :  10.14445/22312803/IJCTT-V68I3P115

How to Cite?

Rochelle Cordeiro, Anol Kurian, Brinel D`souza, Brijmohan Daga, "Automated Training for Job Interviews," International Journal of Computer Trends and Technology, vol. 68, no. 3, pp. 74-79, 2020. Crossref, 10.14445/22312803/IJCTT-V68I3P115

Every individual has to face an interview at least once at some point in their life, but have you ever wondered why one gets rejected even though they satisfy the required educational bars set by companies? Our paper aims at providing a computational framework to analyze supplemental features that go along with subjective knowledge such as facial expressions (e.g., smiles, frowns), language (e.g., word count, textual expression) and prosodic information. The framework aims to be tweakable to suit different companies and their needs by taking technical parameters from previously placed alumni while also checking for coherence with the candidates’ CV. It can thus be used to train candidates to better articulate themselves in an interview.

Convolutional Neural Network, Emotion Recognition, Prosodic Features, Lexical Features, Interview Training

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