Abstract
Reading in a foreign language is a difficult task, especially if the texts presented to readers are chosen without taking into account the reader’s skill level. Foreign language learners need to be presented with reading material suitable to their reading capacities. A basic tool for determining if a text is appropriate to a reader’s level is the assessment of its readability, a measure that aims to represent the human capacities required to comprehend a given text. Readability prediction for a text is an important aspect in the process of teaching and learning, for reading in a foreign language as well as in one’s native language, and continues to be a central area of research and practice. In this paper, we present our approach to readability assessment for Modern Standard Arabic (MSA) as a foreign language. Readability prediction is carried out using the Global Language Online Support System (GLOSS) corpus, which was developed for independent learners to improve their foreign language skills and was annotated with the Interagency Language Roundtable (ILR) scale. In this study, we introduce a frequency dictionary, which was developed to calculate frequency-based features. The approach gives results that surpass the state-of the-art results for Arabic.
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Notes
- 1.
https://gloss.dliflc.edu/. The MSA corpus has undergone some variation in contents over time.
- 2.
The ILR scale (https://www.languagetesting.com/ilr-scale), developed by the U.S. Federal Government, rates language ability uses values 0 to 5, where: Level 0 (no proficiency); Level 1 (elementary proficiency); Level 2 (limited working proficiency); Level 3 (general occupational proficiency); Level 4 (advanced professional proficiency) and Level 5 (functionally native proficiency). Levels 0+, 1+, 2+, 3+, or 4+ are used when the person’s skills significantly exceed those of a given level, but are insufficient to reach the next level.
- 3.
The Waikato Environment for Knowledge Analysis (WEKA) is an open source machine learning software resource that contains implementations of various algorithms.
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Nassiri, N., Lakhouaja, A., Cavalli-Sforza, V. (2018). Arabic Readability Assessment for Foreign Language Learners. In: Silberztein, M., Atigui, F., Kornyshova, E., Métais, E., Meziane, F. (eds) Natural Language Processing and Information Systems. NLDB 2018. Lecture Notes in Computer Science(), vol 10859. Springer, Cham. https://doi.org/10.1007/978-3-319-91947-8_49
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