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Aralex: a lexical database for Modern Standard Arabic.
Sami Boudelaa1, William D Marslen-Wilson
1MRC Cognition and Brain Sciences Unit, Cambridge, England. sami.boudelaa@mrc-cbu.cam.ac.uk
A new lexical database, Aralex, offers frequency data for Modern Standard Arabic roots, patterns, and n-grams. This resource aids cognitive processing studies, natural language processing research, and educational vocabulary development.
Area of Science:
- Computational Linguistics
- Psycholinguistics
- Lexicography
Background:
- Modern Standard Arabic (MSA) research requires robust lexical resources.
- Existing databases may not capture contemporary usage frequencies.
- Cognitive processing and NLP studies benefit from precise word frequency data.
Purpose of the Study:
- Introduce Aralex, a novel lexical database for MSA.
- Provide comprehensive frequency information on roots, word patterns, and n-grams.
- Facilitate research in psycholinguistics, NLP, and education.
Main Methods:
- Compiled a contemporary text corpus of 40 million words.
- Extracted token and type frequencies for roots and word patterns.
- Analyzed frequencies of orthographic and lexical n-grams (bigrams, trigrams).
Main Results:
- Aralex database established with detailed frequency metrics.
- Data includes root/pattern token and type frequencies.
- Includes frequency counts for orthographic and lexical bigrams and trigrams.
Conclusions:
- Aralex serves as a valuable tool for Arabic language research.
- Enables precise stimulus selection for cognitive processing experiments.
- Supports natural language processing applications and educational vocabulary initiatives.
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