  In this paper, we introduce EmpBot: an end-to-end empathetic chatbot.
Empathetic conversational agents should not only understand what is being
discussed, but also acknowledge the implied feelings of the conversation
partner and respond appropriately. To this end, we propose a method based on a
transformer pretrained language model (T5). Specifically, during finetuning we
propose to use three objectives: response language modeling, sentiment
understanding, and empathy forcing. The first objective is crucial for
generating relevant and coherent responses, while the next ones are significant
for acknowledging the sentimental state of the conversational partner and for
favoring empathetic responses. We evaluate our model on the EmpatheticDialogues
dataset using both automated metrics and human evaluation. The inclusion of the
sentiment understanding and empathy forcing auxiliary losses favor empathetic
responses, as human evaluation results indicate, comparing with the current
state-of-the-art.
