Predicting and Eliciting Addressee's Emotion in Online Dialogue
T. Hasegawa, Nobuhiro Kaji, Naoki Yoshinaga, Masashi Toyoda · 2013
While there have been many attempts to estimate the emotion of an addresser from her/his utterance, few studies have ex-plored how her/his utterance affects the emotion of the addressee. This has mo-tivated us to investigate two novel tasks: predicting the emotion of the addressee and generating a response that elicits a specific emotion in the addressee’s mind. We target Japanese Twitter posts as a source of dialogue data and automatically build training data for learning the pre-dictors and generators. The feasibility of our approaches is assessed by using 1099 utterance-response pairs that are built by five human workers. 1