  Empathetic conversational models have been shown to improve user satisfaction
and task outcomes in numerous domains. In Psychology, persona has been shown to
be highly correlated to personality, which in turn influences empathy. In
addition, our empirical analysis also suggests that persona plays an important
role in empathetic conversations. To this end, we propose a new task towards
persona-based empathetic conversations and present the first empirical study on
the impact of persona on empathetic responding. Specifically, we first present
a novel large-scale multi-domain dataset for persona-based empathetic
conversations. We then propose CoBERT, an efficient BERT-based response
selection model that obtains the state-of-the-art performance on our dataset.
Finally, we conduct extensive experiments to investigate the impact of persona
on empathetic responding. Notably, our results show that persona improves
empathetic responding more when CoBERT is trained on empathetic conversations
than non-empathetic ones, establishing an empirical link between persona and
empathy in human conversations.
