  In this paper, we describe a data enhancement method for developing Emily, an
emotion-affective open-domain chatbot. The proposed method is based on
explicitly modeling positively transitioned (PT) sentiment data from multi-turn
dialogues. We construct a dialogue corpus with PT sentiment data and will
release it for public use. By fine-tuning a pretrained dialogue model using the
produced PT-enhanced dialogues, we are able to develop an emotion-affective
open-domain chatbot exhibiting close-to-human performance in various
emotion-affective metrics. We evaluate Emily against a few state-of-the-art
(SOTA) open-domain chatbots and show the effectiveness of the proposed
approach. The corpus is made publicly available.
