Add to ORKGInternational audienceIn 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
Recognizing and regulating human emotion or a wave of riding emotions are a vital life skill as it c...
AbstractEmotional state recognition has become an important topic for human–robot interaction in the...
Speech emotion recognition aims to automatically identify and classify emotions from speech signals....
In this paper, we address the problem of multimodal emotion recognition from multiple physiological ...
Emotion recognition is attracting the attention of the research community due to its multiple applic...
The development of transformer-based models has resulted in significant advances in addressing vario...
International audienceIn order to exploit representations of time-series signals, such as physiologi...
Emotion Recognition is attracting the attention of the research community due to the multiple areas ...
International audienceAutomatic emotion recognition enhance dramatically the development of human/ma...
In this paper we present a multimodal approach for the recognition of eight emotions that integrates...
This thesis investigates the use of deep learning techniques to address the problem of machine under...
Physiological signals are the most reliable form of signals for emotion recognition, as they cannot ...
In this work, I will present our approach of using multi-modal data for recognizing human emotion an...
Physiological Signals are the most reliable form of signals for emotion recognition, as they cannot ...
Affect (emotion) recognition has many applications, such as human assistive robotics, human computer...
Recognizing and regulating human emotion or a wave of riding emotions are a vital life skill as it c...
AbstractEmotional state recognition has become an important topic for human–robot interaction in the...
Speech emotion recognition aims to automatically identify and classify emotions from speech signals....
In this paper, we address the problem of multimodal emotion recognition from multiple physiological ...
Emotion recognition is attracting the attention of the research community due to its multiple applic...
The development of transformer-based models has resulted in significant advances in addressing vario...
International audienceIn order to exploit representations of time-series signals, such as physiologi...
Emotion Recognition is attracting the attention of the research community due to the multiple areas ...
International audienceAutomatic emotion recognition enhance dramatically the development of human/ma...
In this paper we present a multimodal approach for the recognition of eight emotions that integrates...
This thesis investigates the use of deep learning techniques to address the problem of machine under...
Physiological signals are the most reliable form of signals for emotion recognition, as they cannot ...
In this work, I will present our approach of using multi-modal data for recognizing human emotion an...
Physiological Signals are the most reliable form of signals for emotion recognition, as they cannot ...
Affect (emotion) recognition has many applications, such as human assistive robotics, human computer...
Recognizing and regulating human emotion or a wave of riding emotions are a vital life skill as it c...
AbstractEmotional state recognition has become an important topic for human–robot interaction in the...
Speech emotion recognition aims to automatically identify and classify emotions from speech signals....