English

A Call for Standardization and Validation of Text Style Transfer Evaluation

Machine Learning 2023-06-02 v1 Computation and Language

Abstract

Text Style Transfer (TST) evaluation is, in practice, inconsistent. Therefore, we conduct a meta-analysis on human and automated TST evaluation and experimentation that thoroughly examines existing literature in the field. The meta-analysis reveals a substantial standardization gap in human and automated evaluation. In addition, we also find a validation gap: only few automated metrics have been validated using human experiments. To this end, we thoroughly scrutinize both the standardization and validation gap and reveal the resulting pitfalls. This work also paves the way to close the standardization and validation gap in TST evaluation by calling out requirements to be met by future research.

Keywords

Cite

@article{arxiv.2306.00539,
  title  = {A Call for Standardization and Validation of Text Style Transfer Evaluation},
  author = {Phil Ostheimer and Mayank Nagda and Marius Kloft and Sophie Fellenz},
  journal= {arXiv preprint arXiv:2306.00539},
  year   = {2023}
}

Comments

Accepted to Findings of ACL 2023

R2 v1 2026-06-28T10:53:08.747Z