  Emotional Support Conversation aims at reducing the seeker's emotional
distress through supportive response. Existing approaches have two limitations:
(1) They ignore the emotion causes of the distress, which is important for
fine-grained emotion understanding; (2) They focus on the seeker's own mental
state rather than the emotional dynamics during interaction between speakers.
To address these issues, we propose a novel framework CauESC, which firstly
recognizes the emotion causes of the distress, as well as the emotion effects
triggered by the causes, and then understands each strategy of verbal grooming
independently and integrates them skillfully. Experimental results on the
benchmark dataset demonstrate the effectiveness of our approach and show the
benefits of emotion understanding from cause to effect and
independent-integrated strategy modeling.
