Emotion recognition from unimodal to multimodal analysis: A review

The omnipresence of numerous information sources in our daily life brings up new alternatives for emotion recognition in several domains including e-health, e-learning, robotics, and e-commerce. Due to the variety of data, the research area of multimodal machine learning poses special problems for computer scientists; how did the field of emotion recognition progress in each modality and what are the most common strategies for recognizing emotions? What part does deep learning play in this? What is multimodality? How did it progress? What are the methods of information fusion? What are the most used datasets in each modality and in multimodal recognition? We can understand and compare the various methods by answering these questions.