Towards Job Screening and Personality Traits Estimation From Video
Transcriptions
Abstract
The paper built on First Impression Challenge from Chalearn V2 Workshop
on Explainable Computer Vision Multimedia and Job Candidate Screening
Competition CVPR17 by focusing solely on Textual Input in contrast to
other Challenge’s participants who considered video or audio modalities.
Therefore, the paper aims to develop a new deep learning architecture
capable of predicting human personality traits and job interview from
the video transcripts. Several feature representations that involve
statistical and deep learning have contrasted. Our approach achieved the
best score when text modality alone were employed, yielding an average
of 89% score in human personality traits and 89.10% value for job
interview. The research results will help companies and other
organization studying human personality to assess a human personality
using a minimum textual resources from the job candidates