Multimodal Emotion Analytics for E-Learning

E-learning is one of the modes of learning which is gaining popularity nowadays. To analyze the effectiveness of the E-class, there are many ways like feedback at the end of the lecture. But analyzing at the end will not serve the purpose. By analyzing the feedback of the listeners during the class improves the quality of the E-class. This can be achieved by analyzing the face and acoustics of the listeners. In a few cases, the data may not be obtained from both modalities. So, a novel method is proposed which will continue to perform and successfully recognize emotions even when one modality is absent. Product trends can be predicted by using this model for market analysis and ads can be improvised to reach their end target. Thereby, the manufacturers will receive relevant and better product feedback which leads to a rise in product sales. Studying how users view these multimodal posts will be of interest to sociologists and psychologists. The suggested project will provide a platform for publishing research papers in reputed journals, provides an opportunity for manpower training.