TY - GEN
T1 - Unpaired abstract-to-conclusion text style transfer using CycleGANs
AU - Wang, Haotong
AU - Lepage, Yves
AU - Goh, Chooi Ling
N1 - Funding Information:
This work was supported by JSPS KAKENHT Grant Number JP18K11446 entitled: "Natural language processing for academic writing in English".
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/17
Y1 - 2020/10/17
N2 - The availability of paired examples greatly facilitates the task of style transfer by allowing the use of supervised learning. However, our scenario does not enjoy such a condition. We focus on style transfer for academic writing, and examine the possibility of performing style transfer between sentences from the abstract and conclusion sections of a scientific article in the Natural Language Processing field, in both directions. We assume a latent correlation between the abstract and conclusion styles, and construct an unpaired data set. We propose the use of a version of CydeGAN based on transformers to perform the task. Our approach is shown to realize differences in tense or word usage which are characteristic of the different sections.
AB - The availability of paired examples greatly facilitates the task of style transfer by allowing the use of supervised learning. However, our scenario does not enjoy such a condition. We focus on style transfer for academic writing, and examine the possibility of performing style transfer between sentences from the abstract and conclusion sections of a scientific article in the Natural Language Processing field, in both directions. We assume a latent correlation between the abstract and conclusion styles, and construct an unpaired data set. We propose the use of a version of CydeGAN based on transformers to perform the task. Our approach is shown to realize differences in tense or word usage which are characteristic of the different sections.
KW - GANs
KW - Text style transfer
KW - Unpaired data
UR - http://www.scopus.com/inward/record.url?scp=85099749150&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85099749150&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS51025.2020.9263246
DO - 10.1109/ICACSIS51025.2020.9263246
M3 - Conference contribution
AN - SCOPUS:85099749150
T3 - 2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
SP - 435
EP - 440
BT - 2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
Y2 - 17 October 2020 through 18 October 2020
ER -