Abstract

One way to indicate nonverbal cues is by sending emoji (e.g., ), which requires users to make a selection from large lists. Given the growing number of emojis, this can incur user frustration, and instead we propose Face2Emoji, where we use a user’s facial emotional expression to filter out the relevant set of emoji by emotion category. To validate our method, we crowdsourced 15,155 emoji to emotion labels across 308 website visitors, and found that our 202 tested emojis can indeed be classified into seven basic (including Neutral) emotion categories. To recognize facial emotional expressions, we use deep convolutional neural networks, where early experiments show an overall accuracy of 65% on the FER-2013 dataset. We discuss our future research on Face2Emoji, addressing how to improve our model performance, what type of usability test to run with users, and what measures best capture the usefulness and playfulness of our system.