Emotion-aware chat machine: Automatic emotional response generation for human-like emotional interaction

Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

54 Citations (Scopus)

Abstract

The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem by proposing a unified end-to-end neural architecture, which is capable of simultaneously encoding the semantics and the emotions in a post for generating more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed method outperforms the state-of-the-art methods in terms of both content coherence and emotion appropriateness.

Original languageEnglish
Title of host publicationCIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages1401-1410
Number of pages10
ISBN (Electronic)9781450369763
DOIs
Publication statusPublished - 3 Nov 2019
Event28th ACM International Conference on Information and Knowledge Management, CIKM 2019 - Beijing, China
Duration: 3 Nov 20197 Nov 2019

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference28th ACM International Conference on Information and Knowledge Management, CIKM 2019
Country/TerritoryChina
CityBeijing
Period3/11/197/11/19

Keywords

  • Dialogue generation
  • Emotional chatbot
  • Emotional conversation

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