Using Multilingual Bidirectional Encoder Representations from Transformers on Medical Corpus for Kurdish Text Classification

Soran S. Badawi

doi:10.14500/aro.11088

Authors

Soran S. Badawi Charmo Center for Scientific Research and Consulting – Language and Linguistic Center, Charmo University Chamchamal, Sulaimani, Kurdistan region - F.R. Iraq https://orcid.org/0000-0001-9117-3078

DOI:

https://doi.org/10.14500/aro.11088

Keywords:

Bidirectional Encoder Representations from Transformers, Deep learning, Machine learning, Natural language processing, Sentiment analysis, Transformers

Abstract

Technology has dominated a huge part of human life. Furthermore, technology users use language continuously to express feelings and sentiments about things. The science behind identifying human attitudes toward a particular product, service,or topic is one of the most active fields of research, and it is called sentiment analysis. While the English language is making real progress in sentiment analysis daily, other less-resourced languages, such as Kurdish, still suffer from fundamental issues and challenges in Natural Language Processing (NLP). This paper experimentswith the recently published medical corpus using the classical machine learning method and the latest deep learning tool in NLP and Bidirectional Encoder Representations from Transformers (BERT). We evaluated the findings of both machine learning and deep learning. The outcome indicates that BERT outperforms all the machine learning classifiers by scoring (92%) in accuracy, which is by two points higher than machine learning classifiers.

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Author Biography

Soran S. Badawi, Charmo Center for Scientific Research and Consulting – Language and Linguistic Center, Charmo University Chamchamal, Sulaimani, Kurdistan region - F.R. Iraq

Soran S. Badawi is an Assistant Lecturer at the Language Center, Charmo Researcher Center for research, training and consultancy, Charmo University. He got the B.Sc. degree in English Language and Literature at University of Sulaimani, Iraq, and the M.Sc. degree in Computational Linguistics from Isfahan University, Iran. His research interests are in Natural Language Processing (NLP), Machine Translation and Sentiment Analysis.

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