| Autor: |
Daryna Dementieva, Varvara Logacheva, Irina Nikishina, Alena Fenogenova, David Dale, Irina Krotova, Nikita Semenov, Tatiana Shavrina, Alexander Panchenko |
| Rok vydání: |
2022 |
| Zdroj: |
COMPUTATIONAL LINGUISTICS AND INTELLECTUAL TECHNOLOGIES. |
| DOI: |
10.28995/2075-7182-2022-21-114-131 |
| Popis: |
Text detoxification is the task of rewriting a toxic text into a neutral text while preserving its original content. It has a wide range of applications, e.g. moderation of output of neural chatbots or suggesting less emotional version of posts on social networks. This paper provides a description of RUSSE-2022 competition of detoxification methods for the Russian language. This is the first competition which features (i) parallel training data and (ii) manual evaluation. We describe the setup of the competition, the solutions of the participating teams and analyse their performance. In addition to that, the large-scale evaluation allows us to analyse the performance of automatic evaluation metrics. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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