Deep Personality Trait Recognition: A Survey

Abstract

Automatic personality trait recognition has attracted increasing interest in psychology, neuropsychology, and computer science, etc. Motivated by the great success of deep learning methods in various tasks, a variety of deep neural networks have increasingly been employed to learn high-level feature representations for automatic personality trait recognition. This paper systematically presents a comprehensive survey on existing personality trait recognition methods from a computational perspective. Initially, we provide available personality trait data sets in the literature. Then, we review the principles and recent advances of typical deep learning techniques, including deep belief networks (DBNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Next, we describe the details of state-of-the-art personality trait recognition methods with specific focus on hand-crafted and deep learning-based feature extraction. These methods are analyzed and summarized in both single modality and multiple modalities, such as audio, visual, text, and physiological signals. Finally, we analyze the challenges and opportunities in this field and point out its future directions.

Integrating audio and visual modalities for multimodal personality trait recognition via hybrid deep learning

“…In recent years, researchers have employed computational techniques such as machine learning and deep learning methods (Gao et al, 2020;Liang et al, 2021;Wang and Deng, 2021;Yan et al, 2021;Ye et al, 2021) to model and measure human personality from the first impression behavior data, which is called personality computing (Junior et al, 2019). One of the most important research subject in personality computing is automatic personality trait recognition, which aims to identify people's first impression behavior data by computer and then analyze people's psychological characteristics (Zhao et al, 2022). Personality trait recognition has significant applications to human emotional behavior analysis, human-computer interaction, and interview recommendation.…”

“…In a basic personality trait recognition system, two important steps are involved: feature extraction and personality trait classification or prediction (Zhao et al, 2022). Feature extraction aims to derive appropriate feature parameters related to the expression of personality traits from the acquired first impression behavioral data.…”

“…According to the types of extracted features characterizing personality traits, personality trait recognition techniques can be divided into hand-crafted based methods and deep learning based methods. Based on the extracted hand-crafted or deep learning features, previous works (Zhao et al, 2022) focus on performing personality trait recognition from single modality, such as audio-based personality trait recognition (Mohammadi and Vinciarelli, 2012), visual-based personality trait recognition (Gürpınar et al, 2016), etc. Although these works based on single modality have achieved good performance, there are still two limitations for them.…”