查看文章

Dialogue systems, also known as Conversational Agent (CA), are designed to mimic coherent conversations with humans. Most conversational agents are specialized for a specific domain such as travel booking and are typically finite state-based or template-based. Open domain dialogue systems have seen a growing interest in recent years thanks to neural dialogue generation systems, based on deep learning models.

These systems basically learn to predict the words and the sentence to respond based on the previous utterances. However, while such a system can generate grammatically correct and human-like answers, the responses are often generic and non-committal instead of being specific and emotionally intelligent. In this work, the objective is to tackle two main problems that are essential towards building emotionally intelligent chatbots:“How to detect the emotions expressed by the human accurately?” and “How can a chatbot express an emotion?”