This repo contains the code and data of the paper: Leveraging Low-resource Parallel Data for Text Style Transfer.
Our approach: We (1) built a TST system with low-resource parallel data, (2) applied multiple low-resource adaptation techniques, (3) and a novel style reward approach.
pip install -r requirements.txt
Will add more information in this section soon.
If you use this data or code please cite the following:
@inproceedings{mukherjee2023leveraging,
author = {Sourabrata Mukherjee and Ondrej Dusek}, title = { Leveraging Low-Resource Parallel Data for Text Style Transfer}, booktitle = {Proceedings of the 16th International Natural Language Generation Conference}, pages = {388--395}, address = {Prague, Czechia}, year = {2023}, } author = , title = , booktitle = , year = }
Author: Sourabrata Mukherjee
Copyright © 2023 Sourabrata Mukherjee.
Licensed under the MIT License.
This research was supported by Charles University projects GAUK 392221, and SVV 260575, and by the European Research Council (Grant agreement No. 101039303 NG-NLG).