It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books

Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang, Toby Li, Mo Yu, Ying Xu


Abstract
Existing question answering (QA) techniques are created mainly to answer questions asked by humans. But in educational applications, teachers often need to decide what questions they should ask, in order to help students to improve their narrative understanding capabilities. We design an automated question-answer generation (QAG) system for this education scenario: given a story book at the kindergarten to eighth-grade level as input, our system can automatically generate QA pairs that are capable of testing a variety of dimensions of a student’s comprehension skills. Our proposed QAG model architecture is demonstrated using a new expert-annotated FairytaleQA dataset, which has 278 child-friendly storybooks with 10,580 QA pairs. Automatic and human evaluations show that our model outperforms state-of-the-art QAG baseline systems. On top of our QAG system, we also start to build an interactive story-telling application for the future real-world deployment in this educational scenario.
Anthology ID:
2022.acl-long.54
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
731–744
Language:
URL:
https://aclanthology.org/2022.acl-long.54
DOI:
10.18653/v1/2022.acl-long.54
Bibkey:
Cite (ACL):
Bingsheng Yao, Dakuo Wang, Tongshuang Wu, Zheng Zhang, Toby Li, Mo Yu, and Ying Xu. 2022. It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 731–744, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books (Yao et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.54.pdf
Data
FairytaleQAMS MARCONarrativeQAPAQ