Between Denoising and Translation: Experiments in Text Detoxification
Sergey Pletenev · Computational Linguistics and Intellectual Technologies · 2022
This paper describes a solution for the RUSSE Detoxification competition held as part of the Dialogue 2022 conference. The paper presents experiments based on autoregressive and non-autoregressive models. The following approaches are described in this paper: 1) Detoxification as a special case of the text style-transfer problem and the use of modern approaches to solve this task in Russian. 2) Using the Automatic Post-Editing algorithm as a task of translation from toxic to normative Russian text. The article provides an analysis of the listed models, their results in detoxification of sentences, as well an analysis of errors and reasons why the models gave such a diverse result.