Abstract

Answering questions is one method to increase or measure understanding. However, creating relevant and answerable questions from the given context is not easy. Automatic Question Generation (AQG) is a part of Natural Language Processing (NLP) which can generate questions automatically from text input. Many studies related to AQG have been carried out but are still very limited in Indonesian texts, especially those that use the latest Transformer variations. This study proposes an AQG system that utilizes the latest power Transformer, the multilingual Text-to-Text Transfer Transformer (mT5). We fine-tune the mT5 model to extract answers from context and generate questions based on those answers. We use the Indonesian dataset extracted from the TyDiQA dataset and evaluate this model against the TyDiQA validation set using BLEU (BiLingual Evaluation Understudy) and ROUGE (Recall-Oriented Understudy for Gisting Evaluation) metrics. This model achieved BLEU-1, BLEU-2, BLEU-3, BLEU-4, and ROUGE-L scores of 36.54, 28.24, 22.61, 18.44, and 39.57, respectively. Our model performs well and generates questions in understandable Indonesian with good word choice and grammar based on manual validation.

Original languageEnglish
Title of host publicationProceedings - IEIT 2022
Subtitle of host publication2022 International Conference on Electrical and Information Technology
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages84-89
Number of pages6
ISBN (Electronic)9781665453035
DOIs
Publication statusPublished - 2022
Event2022 International Conference on Electrical and Information Technology, IEIT 2022 - Malang, Indonesia
Duration: 15 Sept 202216 Sept 2022

Publication series

NameProceedings - IEIT 2022: 2022 International Conference on Electrical and Information Technology

Conference

Conference2022 International Conference on Electrical and Information Technology, IEIT 2022
Country/TerritoryIndonesia
CityMalang
Period15/09/2216/09/22

Keywords

  • AQG
  • Transformer
  • mT5
  • question generation

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