SentEmojiBot: Empathising Conversations Generation with Emojis
This addresses the need for more human-like emotional expression in dialogue agents, though it is incremental as it builds on existing methods with a new dataset.
The paper tackled the problem of generating empathetic conversations by incorporating emojis, achieving a 9.8% improvement in empathetic traits through a BERT-based model.
The increasing use of dialogue agents makes it extremely desirable for them to understand and acknowledge the implied emotions to respond like humans with empathy. Chatbots using traditional techniques analyze emotions based on the context and meaning of the text and lack the understanding of emotions expressed through face. Emojis representing facial expressions present a promising way to express emotions. However, none of the AI systems utilizes emojis for empathetic conversation generation. We propose, SentEmojiBot, based on the SentEmoji dataset, to generate empathetic conversations with a combination of emojis and text. Evaluation metrics show that the BERT-based model outperforms the vanilla transformer model. A user study indicates that the dialogues generated by our model were understandable and adding emojis improved empathetic traits in conversations by 9.8%