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TU Berlin

Inhalt des Dokuments

Salar Mohtaj


Research Field

- Natural Language Processing
- Machine Learning
- Information Retrieval

 Research Topics

- 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
TU Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany

Email: salar.mohtaj[at]tu-berlin.de
Tel:  +49 30 8353 58394




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.
Link zur Publikation Link zur Originalpublikation Download Bibtex Eintrag

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