TensorFlow-Based Automatic Personality Recognition Used in Asynchronous Video Interviews

Hung Yue Suen, Kuo En Hung, Chien Liang Lin*

*此作品的通信作者

研究成果: 雜誌貢獻回顧評介論文同行評審

14 引文 斯高帕斯(Scopus)

摘要

With the development of artificial intelligence (AI), the automatic analysis of video interviews to recognize individual personality traits has become an active area of research and has applications in personality computing, human-computer interaction, and psychological assessment. Advances in computer vision and pattern recognition based on deep learning (DL) techniques have led to the establishment of convolutional neural network models that can successfully recognize human nonverbal cues and attribute their personality traits with the use of a camera. In this paper, an end-to-end AI interviewing system was developed using asynchronous video interview (AVI) processing and a TensorFlow AI engine to perform automatic personality recognition (APR) based on the features extracted from the AVIs and the true personality scores from the facial expressions and self-reported questionnaires of 120 real job applicants. The experimental results show that our AI-based interview agent can successfully recognize the 'big five' traits of an interviewee at an accuracy between 90.9% and 97.4%. Our experiment also indicates that although the machine learning was conducted without large-scale data, the semisupervised DL approach performed surprisingly well with regard to APR despite the lack of labor-intensive manual annotation and labeling. The AI-based interview agent can supplement or replace existing self-reported personality assessment methods that job applicants may distort to achieve socially desirable effects.

原文英語
文章編號8660507
頁(從 - 到)61018-61023
頁數6
期刊IEEE Access
7
DOIs
出版狀態已發佈 - 2019

ASJC Scopus subject areas

  • 電腦科學(全部)
  • 材料科學(全部)
  • 工程 (全部)

指紋

深入研究「TensorFlow-Based Automatic Personality Recognition Used in Asynchronous Video Interviews」主題。共同形成了獨特的指紋。

引用此