CAiRE: An End-to-End Empathetic Chatbot

  • Zhaojiang Lin The Hong Kong University of Science and Technology
  • Peng Xu The Hong Kong University of Science and Technology
  • Genta Indra Winata The Hong Kong University of Science and Technology
  • Farhad Bin Siddique The Hong Kong University of Science and Technology
  • Zihan Liu The Hong Kong University of Science and Technology
  • Jamin Shin The Hong Kong University of Science and Technology
  • Pascale Fung The Hong Kong University of Science and Technology

Abstract

We present CAiRE, an end-to-end generative empathetic chatbot designed to recognize user emotions and respond in an empathetic manner. Our system adapts the Generative Pre-trained Transformer (GPT) to empathetic response generation task via transfer learning. CAiRE is built primarily to focus on empathy integration in fully data-driven generative dialogue systems. We create a web-based user interface which allows multiple users to asynchronously chat with CAiRE. CAiRE also collects user feedback and continues to improve its response quality by discarding undesirable generations via active learning and negative training.

Published
2020-04-03