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A Multi-Turn Emotionally Engaging Dialog Model
[article]
2020
arXiv
pre-print
Open-domain dialog systems (also known as chatbots) have increasingly drawn attention in natural language processing. Some of the recent work aims at incorporating affect information into sequence-to-sequence neural dialog modeling, making the response emotionally richer, while others use hand-crafted rules to determine the desired emotion response. However, they do not explicitly learn the subtle emotional interactions captured in human dialogs. In this paper, we propose a multi-turn dialog
arXiv:1908.07816v3
fatcat:jax6zgnxdfextg7f2zrsmhyiei