  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.
