Experimental Comparison of Machine Learning Techniques for Analysing the Facial Expression

Abstract

Emoticons are miniature pictures that are customarily used in internet community Communications in the 21st century. The fusion of textual and imagery contained in the same message develops today's modern way of conversation. In spite of being universally utilized in online media, Emoticons basic interpretation has received very little observation from a “Natural Language Processing” point of view. In this paper, we investigate the relation between facial expressions and emoticons, studying the novel task of predicting which emojis are evoked by the user's facial expressions. We experimented with variants of word embedding techniques, and train various models based on MNBs and LSTMs in this task respectively. The experimental results show that our model can predict reasonable emoticons from emotions.