Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer

Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, Marine Carpuat


Abstract
While the field of style transfer (ST) has been growing rapidly, it has been hampered by a lack of standardized practices for automatic evaluation. In this paper, we evaluate leading automatic metrics on the oft-researched task of formality style transfer. Unlike previous evaluations, which focus solely on English, we expand our focus to Brazilian-Portuguese, French, and Italian, making this work the first multilingual evaluation of metrics in ST. We outline best practices for automatic evaluation in (formality) style transfer and identify several models that correlate well with human judgments and are robust across languages. We hope that this work will help accelerate development in ST, where human evaluation is often challenging to collect.
Anthology ID:
2021.emnlp-main.100
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1321–1336
Language:
URL:
https://aclanthology.org/2021.emnlp-main.100
DOI:
10.18653/v1/2021.emnlp-main.100
Bibkey:
Cite (ACL):
Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, and Marine Carpuat. 2021. Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1321–1336, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer (Briakou et al., EMNLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-acl-2023-videos/2021.emnlp-main.100.pdf
Video:
 https://preview.aclanthology.org/ingest-acl-2023-videos/2021.emnlp-main.100.mp4
Code
 fuzhenxin/Style-Transfer-in-Text +  additional community code
Data
GYAFCOpenSubtitles