EmoBot: Artificial emotion generation through an emotional chatbot during general-purpose conversations

Abstract

Emotion modeling has always been intriguing to researchers, where detecting emotion is highly focused and generating emotion is much less focused to date. Therefore, in this paper, we aim to exploring emotion generation, particularly for general-purpose conversations. Based on the Cognitive Appraisal Theory and focusing on audio and textual inputs, we propose a novel method to calculate informative variables to evaluate a particular emotion-generating event and six primary emotions. Incorporating such a method of artificial emotion generation, we implement an emotional chatbot, namely EmoBot. Accordingly, EmoBot analyzes continuous audio and textual inputs, calculates the informative variables to evaluate the current situation, generates appropriate emotions, and responds accordingly. An objective evaluation indicates that EmoBot could generate more accurate emotional and semantic responses than a traditional chatbot that does not consider emotion. Additionally, a subjective evaluation of EmoBot demonstrates the appreciation of users for EmoBot over a traditional chatbot that does not consider emotion.