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In communication, a human would recognize the emotion of an interlocutor andrespond with an appropriate emotion, such as empathy and comfort. Towarddeveloping a dialogue system with such a human-like ability, we propose amethod to build a dialogue corpus annotated with two kinds of emotions. Wecollect dialogues from Twitter and annotate each utterance with the emotionthat a speaker put into the utterance (expressed emotion) and the emotion thata listener felt after listening to the utterance (experienced emotion). Webuilt a dialogue corpus in Japanese using this method, and its statisticalanalysis revealed the differences between expressed and experienced emotions.We conducted experiments on recognition of the two kinds of emotions. Theexperimental results indicated the difficulty in recognizing experiencedemotions and the effectiveness of multi-task learning of the two kinds ofemotions. We hope that the constructed corpus will facilitate the study onemotion recognition in a dialogue and emotion-aware dialogue responsegeneration.

Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions