Inhalt des Dokuments
- © Copyright??
- Natural Language Processing
- Machine Learning
- Information Retrieval
- Text quality assessment
Salar is a researcher at the Quality and Usability Lab at
Technische Universitat Berlin working on natural language processing
applications in crowdsourcing.
His main interest is NLP and machine learning models. He received his bachelor degree from Shahrood University of Technology and master in information technology from AmirKabir University of Technology (Tehran Polytechnic).
Quality and Usability Lab
Deutsche Telekom Laboratories
D-10587 Berlin, Germany
Tel: +49 30 8353 58394
|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.|
|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.|