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A Hybrid Framework of Emotion-Aware Seq2Seq Model for Emotional Conversation Generation

  • Xiaohe Li
  • Jiaqing Liu
  • Weihao Zheng
  • Xiangbo Wang
  • Yutao Zhu
  • Zhicheng DouEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11966)

Abstract

This paper describes RUCIR’s system in NTCIR-14 Short Text Conversation (STC) Chinese Emotional Conversation Generation (CECG) subtask. In our system, we use the Attention-based Sequence-to-Sequence (Seq2Seq) method as our basic structure to generate emotional responses. This paper introduces (1) an emotion-aware Seq2Seq model and (2) several features to boost the performance of emotion consistency. Official results show that our model performs the best in terms of the overall results across the five given emotion categories.

Keywords

Emotional Conversation Generation Sequence to sequence model Attention mechanism Copy mechanism 

Notes

Acknowledgements

Zhicheng Dou is the corresponding author. This work was supported by National Key R&D Program of China No. 2018YFC0830703, National Natural Science Foundation of China No. 61872370, and the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China No. 2112018391.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Xiaohe Li
    • 1
  • Jiaqing Liu
    • 1
  • Weihao Zheng
    • 1
  • Xiangbo Wang
    • 1
  • Yutao Zhu
    • 1
  • Zhicheng Dou
    • 1
    Email author
  1. 1.School of InformationRenmin University of ChinaBeijingChina

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