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Empathy is a complex cognitive ability based on the reasoning of others'affective states. In order to better understand others and express strongerempathy in dialogues, we argue that two issues must be tackled at the sametime: (i) identifying which word is the cause for the other's emotion from hisor her utterance and (ii) reflecting those specific words in the responsegeneration. However, previous approaches for recognizing emotion cause words intext require sub-utterance level annotations, which can be demanding. Takinginspiration from social cognition, we leverage a generative estimator to inferemotion cause words from utterances with no word-level label. Also, weintroduce a novel method based on pragmatics to make dialogue models focus ontargeted words in the input during generation. Our method is applicable to anydialogue models with no additional training on the fly. We show our approachimproves multiple best-performing dialogue agents on generating more focusedempathetic responses in terms of both automatic and human evaluation.

Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes