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Emotional support is a crucial skill for many real-world scenarios, includingcaring for the elderly, mental health support, and customer service chats. Thispaper presents a novel task of empathetic dialog generation with positiveemotion elicitation to promote users' positive emotions, similar to that ofemotional support between humans. In this task, the agent conducts empatheticresponses along with the target of eliciting the user's positive emotions inthe multi-turn dialog. To facilitate the study of this task, we collect alarge-scale emotional dialog dataset with positive emotion elicitation, calledPosEmoDial (about 820k dialogs, 3M utterances). In these dialogs, the agenttries to guide the user from any possible initial emotional state, e.g.,sadness, to a positive emotional state. Then we present apositive-emotion-guided dialog generation model with a novel loss functiondesign. This loss function encourages the dialog model to not only elicitpositive emotions from users but also ensure smooth emotional transitions alongwith the whole dialog. Finally, we establish benchmark results on PosEmoDial,and we will release this dataset and related source code to facilitate futurestudies.

Towards Multi-Turn Empathetic Dialogs with Positive Emotion Elicitation