Papers › HIIG at GermEval 2022: Best of Both Worlds Ensemble for Automatic Text Complexity Assessment
HIIG at GermEval 2022: Best of Both Worlds Ensemble for Automatic Text Complexity Assessment
Hadi Asghari, Freya Hewett
In this paper we explain HIIG’s contribution to the shared task Text Complexity DE Challenge 2022. Our best-performing model for the task of automatically determining the complexity level of a German-language sentence is a combination of a transformer model and a classic feature-based model, which achieves a mapped root square mean error of 0.446 on the test data.
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