JOURNAL ARTICLE

CAiRE: An End-to-End Empathetic Chatbot

Zhaojiang LinPeng XuGenta Indra WinataZihan LiuPascale FungJamin ShinPascale Fung

Year: 2020 Journal:   Proceedings of the AAAI Conference on Artificial Intelligence Vol: 34 (09)Pages: 13622-13623   Publisher: Association for the Advancement of Artificial Intelligence

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.

Keywords:
End-to-end principle Chatbot End user End of history Computer science World Wide Web Computer security Political science

Metrics

14
Cited By
1.32
FWCI (Field Weighted Citation Impact)
1
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

AI in Service Interactions
Physical Sciences →  Computer Science →  Artificial Intelligence
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