research-article

Towards Automated Emotional Conversation Generation with Implicit and Explicit Affective Strategy

Authors:

Si LiAuthors Info & Claims

SSPS '19: Proceedings of the 2019 International Symposium on Signal Processing Systems

Pages 125 - 130

https://doi.org/10.1145/3364908.3365288

Published: 20 September 2019 Publication History

Abstract

Building an empathic conversation machine in open-domain is a promising research topic in natural language processing. However, most current approaches rely on designated emotions to conduct generating responses and lack the ability to decide the appropriate emotion strategy. In this paper, we propose a dialogue model of jointly predicting and generating emotions called DRCVAE, which stands for Decoupled Representations of Conditional Variational Autoencoders.

More specifically, the model separates the latent variable in conditional variational autoencoders (CVAE) into two parts: emotion and content. Then the latent emotional strategy (implicit) is further forced to predict the target emotion probability distribution (explicit). By using implicit and explicit emotional strategy, a newly designed paired decoder incorporates rich control information to decode the response. Experiment results demonstrate that DRCVAE provides an effective way to infer target emotions and generate high-quality responses simultaneously.

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Cited By

Poria SHazarika DMajumder NMihalcea R(2023)Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis ResearchIEEE Transactions on Affective Computing10.1109/TAFFC.2020.303816714:1(108-132)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TAFFC.2020.3038167

Index Terms

Towards Automated Emotional Conversation Generation with Implicit and Explicit Affective Strategy
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Discourse, dialogue and pragmatics

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SSPS '19: Proceedings of the 2019 International Symposium on Signal Processing Systems

September 2019

188 pages

ISBN:9781450362412

DOI:10.1145/3364908

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Beijing University of Posts and Telecommunications

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New York, NY, United States

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Published: 20 September 2019

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SSPS 2019: 2019 International Symposium on Signal Processing Systems

September 20 - 22, 2019

Beijing, China

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Cited By

Poria SHazarika DMajumder NMihalcea R(2023)Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis ResearchIEEE Transactions on Affective Computing10.1109/TAFFC.2020.303816714:1(108-132)Online publication date: 1-Jan-2023
https://doi.org/10.1109/TAFFC.2020.3038167

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