Emotion Recognition with Pre-Trained Transformers Using Multimodal Signals

12/22/2022
by   Juan Vazquez-Rodriguez, et al.
0

In this paper, we address the problem of multimodal emotion recognition from multiple physiological signals. We demonstrate that a Transformer-based approach is suitable for this task. In addition, we present how such models may be pretrained in a multimodal scenario to improve emotion recognition performances. We evaluate the benefits of using multimodal inputs and pre-training with our approach on a state-ofthe-art dataset.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/27/2021

MEmoBERT: Pre-training Model with Prompt-based Learning for Multimodal Emotion Recognition

Multimodal emotion recognition study is hindered by the lack of labelled...
research
11/29/2019

Multimodal Emotion Recognition Model using Physiological Signals

As an important field of research in Human-Machine Interactions, emotion...
research
05/20/2022

A Survey on Physiological Signal Based Emotion Recognition

Physiological Signals are the most reliable form of signals for emotion ...
research
06/05/2023

Interpretable Multimodal Emotion Recognition using Facial Features and Physiological Signals

This paper aims to demonstrate the importance and feasibility of fusing ...
research
08/23/2023

Multimodal Latent Emotion Recognition from Micro-expression and Physiological Signals

This paper discusses the benefits of incorporating multimodal data for i...
research
02/20/2023

Knowledge-aware Bayesian Co-attention for Multimodal Emotion Recognition

Multimodal emotion recognition is a challenging research area that aims ...
research
05/04/2023

Noise-Resistant Multimodal Transformer for Emotion Recognition

Multimodal emotion recognition identifies human emotions from various da...

Please sign up or login with your details

Forgot password? Click here to reset