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Learning to Converse Emotionally Like Humans: A Conditional Variational Approach

  • Rui Zhang
  • Zhenyu WangEmail author
Conference paper
  • 1.3k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11108)

Abstract

Emotional intelligence is one of the key parts of human intelligence. Exploring how to endow conversation models with emotional intelligence is a recent research hotspot. Although several emotional conversation approaches have been introduced, none of these methods were able to decide an appropriate emotion category for the response. We propose a new neural conversation model which is able to produce reasonable emotion interaction and generate emotional expressions. Experiments show that our proposed approaches can generate appropriate emotion and yield significant improvements over the baseline methods in emotional conversation.

Keywords

Emotion selection Emotional conversation 

Notes

Acknowledgements

This work is supported by the Science and Technology Program of Guangzhou, China(No. 201802010025), the Fundamental Research Funds for the Central Universities(No. 2017BQ024), the Natural Science Foundation of Guangdong Province(No. 2017A030310428) and the University Innovation and Entrepreneurship Education Fund Project of Guangzhou(No. 2019PT103). The authors also thank the editors and reviewers for their constructive editing and reviewing, respectively.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Software EngineeringSouth China University of TechnologyGuangzhouPeople’s Republic of China

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