Conditional Sentence Rephrasing without Parallel Training Corpus

Yen Ting Lee, Cheng Te Li, Shou De Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper aims to rephrase a sentence with a given condition, and the generated sentence should be similar to the origin sentence and satisfy the given condition without parallel training corpus. We propose a conditional sentence VAE (CS-VAE) model to solve the task. CS-VAE is trained as an autoencoder, along with the condition control on the generated sentence with the same semantics. With the experimental demonstration supported, CS-VAE is proven to effectively solve the task with high-quality sentences.

Original languageEnglish
Title of host publicationICMEW 2022 - IEEE International Conference on Multimedia and Expo Workshops 2022, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665472180
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2022 - Taipei City, Taiwan
Duration: 2022 Jul 182022 Jul 22

Publication series

NameICMEW 2022 - IEEE International Conference on Multimedia and Expo Workshops 2022, Proceedings

Conference

Conference2022 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2022
Country/TerritoryTaiwan
CityTaipei City
Period22-07-1822-07-22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Media Technology

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