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.
@article{arxiv.2212.13885,
title = {Emotion Recognition with Pre-Trained Transformers Using Multimodal Signals},
author = {Juan Vazquez-Rodriguez and Grégoire Lefebvre and Julien Cumin and James L Crowley},
journal= {arXiv preprint arXiv:2212.13885},
year = {2022}
}