Personality Trait Recognition
4 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Personality Trait Recognition
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CPED
Essays
Latest papers with no code
Personality Trait Recognition using ECG Spectrograms and Deep Learning
This paper presents an innovative approach to recognizing personality traits using deep learning (DL) methods applied to electrocardiogram (ECG) signals.
Automatic Personality Prediction; an Enhanced Method Using Ensemble Modeling
Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.).
Recent Trends in Deep Learning Based Personality Detection
This review paper provides an overview of the most popular approaches to automated personality detection, various computational datasets, its industrial applications, and state-of-the-art machine learning models for personality detection with specific focus on multimodal approaches.
Modality-based Factorization for Multimodal Fusion
We propose a novel method, Modality-based Redundancy Reduction Fusion (MRRF), for understanding and modulating the relative contribution of each modality in multimodal inference tasks.
First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis
However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data.
A Recurrent and Compositional Model for Personality Trait Recognition from Short Texts
Many methods have been used to recognise author personality traits from text, typically combining linguistic feature engineering with shallow learning models, e. g. linear regression or Support Vector Machines.
A Language-independent and Compositional Model for Personality Trait Recognition from Short Texts
Many methods have been used to recognize author personality traits from text, typically combining linguistic feature engineering with shallow learning models, e. g. linear regression or Support Vector Machines.
