An approach to automatic answering for English reading comprehension tests

Authors

  • Phat Tien Bui
    Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam
  • Hieu Chi Tran
    Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam
  • Thanh Huu Duong
    Ho Chi Minh City Open University, Ho Chi Minh City, Viet Nam

DOI:

10.46223/HCMCOUJS.tech.en.14.2.2917.2024

Keywords:

BERT; multiple choice; Masked Language Model (MLM); Question Answering (QA); tokenization; transformer; word embeddings

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.

Downloads

Download data is not yet available.

References

Bordes, A., Chopra, S., & Weston, J. (2014). Question answering with subgraph embeddings. Retrieved May 10, 2023 from https://arxiv.org/pdf/1406.3676.pdf

Chen, D., Bolton, J., & Manning, C. D. (2016). A thorough examination of the CNN/Daily mail reading comprehension task. Retrieved May 10, 2023 from https://arxiv.org/pdf/1606.02858.pdf

Chen, Q., Zhuo, Z., & Wang, W. (2019). BERT for joint intent classification and slot filling. Retrieved May 10, 2023 from https://arxiv.org/pdf/1902.10909.pdf

Devlin, J., Chang, M., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of deep bidirectional transformers for language understanding. Retrieved May 10, 2023 from https://arxiv.org/pdf/1810.04805.pdf

Dodge, J., Ilharco, G., Schwartz, R., Farhadi, A., Hajishirzi, H., & Smith, N. A. (2020). Fine-tuning pretrained language models: Weight initializations, data orders, and early stopping. Retrieved May 10, 2023 from https://arxiv.org/pdf/2002.06305.pdf

Downloads

Received: 20-08-2023
Accepted: 26-02-2024
Published: 04-09-2024

Statistics Views

Abstract: 335
PDF: 269

How to Cite

Bui, P. T., Tran, H. C., & Duong, T. H. (2024). An approach to automatic answering for English reading comprehension tests. Ho Chi Minh City Open University Journal of Science - Engineering and Technology, 14(2), 58–67. https://doi.org/10.46223/HCMCOUJS.tech.en.14.2.2917.2024

Similar Articles

You may also start an advanced similarity search for this article.