Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
11-2019
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.
Keywords
Dialogue generation, Emotional chatbot, Emotional conversation
Discipline
Artificial Intelligence and Robotics | Theory and Algorithms
Research Areas
Data Science and Engineering
Publication
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, Beijing, November 3-7
First Page
1404
Last Page
1410
ISBN
9781450369763
Identifier
10.1145/3357384.3357937
Publisher
ACM
City or Country
New York
Citation
WEI, Wei; LIU, Jiayi; MAO, Xianling; GUO, Guibing; ZHU, Feida; ZHOU, Pan; and HU, Yuchong.
Emotion-aware chat machine: Automatic emotional response generation for human-like emotional interaction. (2019). CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, Beijing, November 3-7. 1404-1410.
Available at: https://ink.library.smu.edu.sg/sis_research/4842
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3357384.3357937
