Li, X., Chen, G., Lin, C. orcid.org/0000-0003-3454-2468 et al. (1 more author) (2020) DGST : a dual-generator network for text style transfer. In: Webber, B., Cohn, T., He, Y. and Liu, Y., (eds.) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 16-20 Nov 2020, Virtual conference. Association for Computational Linguistics (ACL) , pp. 7131-7136. ISBN 9781952148606
Abstract
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our model employs two generators only, and does not rely on any discriminators or parallel corpus for training. Both quantitative and qualitative experiments on the Yelp and IMDb datasets show that our model gives competitive performance compared to several strong baselines with more complicated architecture designs.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Editors: |
|
Copyright, Publisher and Additional Information: | © 2020 Association for Computational Linguistics. Licensed on a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Aug 2021 09:53 |
Last Modified: | 13 Aug 2021 09:53 |
Published Version: | https://aclanthology.org/2020.emnlp-main.578 |
Status: | Published |
Publisher: | Association for Computational Linguistics (ACL) |
Refereed: | Yes |
Identification Number: | 10.18653/v1/2020.emnlp-main.578 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177036 |