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A Dataset for Subjective Assessment of German Text Complexity
Zitatschlüssel mohtaj2019b
Autor Mohtaj, Salar and Naderi, Babak and Ensikat, Kaspar and Möller, Sebastian
Buchtitel Dialog for Good (DiGo), Workshop on Speech and Language Technology Serving Society, Stockholm, 10 September, 2019.
Seiten 1–6
Jahr 2019
Monat sep
Notiz online
Wie herausgegeben Fullpaper
Zusammenfassung This paper presents TextComplexityDE, a text readability assessment dataset consisting of 1000 sentences in German that taken from 23 Wikipedia articles. The corpus could be used for developing text complexity predictors and automatic German text simplification. Text complexity predictor models have diverse applications such as choosing appropriate reading materials for people with intellectual disabilities. The dataset includes subjective assessment of different text-complexity aspects provided by German learners in level A to C. In addition, it contains manual simplification of 250 of those sentences provided by native speakers and subjective assessment of the simplified sentences by participants from the target group.
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