Utilising Natural Language Processing to Assist ESL Learners in Understanding Parts of Speech
- 1. Business Management and Languages, Faculty of Management Science, Silpakorn University, Petchaburi, 76120, Thailand.
- 2. Department of Biology, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand.
Contributors
Contact person:
- 1. Department of Biology, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand.
Description
Abstract: The field of Natural Language Processing (NLP) is growing rapidly, as is the number of companies investing in this technology. NLP is changing the way we learn and teach languages. However, it has not been used in ways that benefit ESL (English as a Second Language) educators. It is implied that there is a gap in the application and the use of an NLP tool that focuses on English Part of Speech (POS) analysis to aid the English teaching and learning process. Herein, in this paper, we discuss the prospect of utilising POS analyser to accommodate ESL educators in teaching English POS. The tool development is divided into two sections: 1) the development of a POS analyser; and 2) the implementation of an interface to make the tool become a user-friendly application. We use SpaCy, an NLP opensource library, for the English POS analysis. It offers both statistical and neural network models. It also comes with pre-trained models that can predict the POS. This paper also provides Graphical User Interface (GUI) tool that can be used to create effective and engaging English language teaching materials for learners. GUI tool is created using python programming language. Thus, we first review the NLP-based applications for ESL education, followed by an introduction and overview of our simple POS analysis tool, which is customizable. In the future, we intend to evaluate our tool with the help of ESL educators who are not computer scientists or linguists. The python script used to develop tool is provided at Github: https://github.com/yashmgupta/literate-robot
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- Journal article: 2278-3075 (ISSN)
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Subjects
- ISSN: 2278-3075 (Online)
- https://portal.issn.org/resource/ISSN/2278-3075#
- Retrieval Number: 100.1/ijitee.E98520411522
- https://www.ijitee.org/portfolio-item/E98520411522/
- Journal Website: www.ijitee.org
- https://www.ijitee.org
- Publisher: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
- https://www.blueeyesintelligence.org