An approach to automatic answering for English reading comprehension tests
Phat Tien Bui,
Hieu Chi Tran and
Thanh Huu Duong
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Phat Tien Bui: Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam
Hieu Chi Tran: Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam
Thanh Huu Duong: Ho Chi Minh City Open University, Ho Chi Minh City, Vietnam
HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, 2024, vol. 14, issue 2, 58-67
Abstract:
This study focuses on the reading comprehension problem with multiple-choice answers, using the BERT model to achieve the highest performance. The ultimate goal is to create a solution to help solve reading comprehension problems without any reasoning or knowledge, suitable for the level of students in grades six and seven. The model will solve factoid questions from a given text. Our research topic will use a deep learning model-based approach to create a model that automatically answers the English reading comprehension question. We obtain promising results to give an accuracy of 78 percent.
Keywords: BERT; multiple choice; Masked Language Model (MLM); Question Answering (QA); tokenization; transformer; word embeddings (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:bjw:techen:v:14:y:2024:i:2:p:58-67
DOI: 10.46223/HCMCOUJS.tech.en.14.2.2917.2024
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