Topic aware context modelling for dialogue response generation

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

Abstract

Response generation is an important direction in conversation systems. Currently a lot of approaches have been proposed and achieved significant improvement. However, an important limitation has been widely realized as most models tend to generate general answers. To cope with this limitation, besides the needs of more sophisticated generation models, how to use extra information is also an important direction. In this research, inspired by the importance of topics in conversation, we proposed a topic aware context modelling framework by utilizing similar question answer pairs in the repository. Furthermore, we use adversarial learning to improve the quality of generated response. The experimental study has shown the propose framework’s potential.

Original languageEnglish
Title of host publicationNeural Information Processing - 26th International Conference, ICONIP 2019, Proceedings
EditorsTom Gedeon, Kok Wai Wong, Minho Lee
PublisherSpringer
Pages387-397
Number of pages11
ISBN (Print)9783030367176
DOIs
StatePublished - 2019
Event26th International Conference on Neural Information Processing, ICONIP 2019 - Sydney, Australia
Duration: 12 Dec 201915 Dec 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11955 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Neural Information Processing, ICONIP 2019
Country/TerritoryAustralia
CitySydney
Period12/12/1915/12/19

Keywords

  • Adversarial
  • Context
  • Dialogue response
  • Topic

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